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Category: DevOps Onramp

  • 5 Reasons to Adopt DevOps

    5 Reasons to Adopt DevOps

    DevOps IT methodologies are taking the development industry by storm. Some call DevOps great for software development. Others find it ideal for pushing out regular software updates and pursuing continuous delivery for clients.

    If you do not know what DevOps is or why your business should adopt DevOps, read on. We’ll break down five reasons why your organization should adopt DevOps at the earliest opportunity.

    What is DevOps?

    In a nutshell, DevOps is short for “development” and “operations.” It’s a software development and programming methodology that helps teams execute ideas more quickly and pursue continuous deployment for organizations and clients. In web and mobile app development, DevOps can be very beneficial thanks to its agility, responsiveness, and versatility.

    Many organizations think of DevOps as some new approach or technology, but it’s actually been around for some time. This approach to IT delivery combines special practices, philosophies, and tools to help mitigate bottlenecks from operations and development.

    Specifically, DevOps combines both development and operations principles to some extent. In this way, most of the major aspects of software or app development are unified. This, in turn, allows teams to respond more capably to shifting project demands and bugs.

    Furthermore, DevOps focuses on organizing and separating “silos” in organizations. In this way, teams or individual workers can take responsibility for a given project. This is superior to separating tasks by individual roles or team labels. DevOps’ advantages mean it’s being used in many different and unique industries, from fintech to medical communication services, and manufacturing.

    However, many businesses are wary about switching to DevOps or any other methodology because it:

    • Requires a major culture switch in workers. It is never easy to shift methodologies, especially when the methodology in question is as complex as DevOps.
    • It is not a one-size-fits-all solution. For DevOps to be successful, your team has to embrace it thoroughly, understand and master its principles, and spend some time practicing.

    Even with these potential downsides, it’s still a very good idea to get your team on board with shifting to DevOps sooner rather than later. Many competing organizations have already done this!

    Benefits of DevOps for Businesses

    DevOps can provide numerous important advantages for businesses just like yours, regardless of industry, niche, or size. Let’s take a look at the five big advantages one by one.

    Better Team Collaboration

    For starters, DevOps often leads to increased team collaboration. Specifically, it allows your development and operations teams or departments to communicate and collaborate much more easily than before.

    In turn, this translates into freer communication between both departments and more trust between individual team members. Your development and operations teams can share their inputs, knowledge, and specific understandings of tools, code, or client desires.

    Think of DevOps as unifying the two teams in your organization. A unified team is one that’s better prepared to respond to changing industry trends, new consumer tastes, or sudden objective shifts that you can’t avoid.

    DevOps is so good at fostering team collaboration because it’s an agile methodology. Agile methodologies are ideal for simplifying complex tasks into more manageable or smaller pieces. This results in a more iterative, manageable planning and development process across the board.

    Greater Security

    DevOps may also lead to greater developmental security. DevSecOps, a broader version of DevOps, involves merging your development and operations teams with your security team.

    In essence, you shift security focuses and practices to the left of your development pipeline. Security checks, cloud monitoring, and regular examinations of code to prevent breaches or vulnerabilities happen earlier in the development process as opposed to later, closer to launch (and when problems or bugs are always harder to fix).

    DevSecOps lets your team identify and fix security issues earlier and more regularly. Any software products or apps your team puts out should be tighter in terms of code security and should be harder to breach or break by any bad actors or hackers.

    Improved Efficiency

    DevOps is very beneficial for organizations because it can improve efficiency in many key ways. DevOps culture and methodologies often require you to use automated tools such as Docker, Git, AWS, and more.

    With these automated tools, your DevOps team can quickly identify bottlenecks or potential issues and take corrective actions as needed without having to waste time. Remember, DevOps inherently means that your teams are more collaborative and communicative, so you don’t need to spend time sending messages between both departments unnecessarily.

    DevOps is very high velocity, infusing your development team with more agility and flexibility than ever before. Naturally, this is a majorly competitive advantage; it allows your team to iterate and innovate more rapidly and regularly than your competitors.

    Faster Bug Resolution

    However, DevOps can also prove advantageous to your organization by helping your company solve discovered bugs more quickly. CI or continuous integration is a core element in any DevOps team or department.

    In a nutshell, this involves checking the final build and any related code regularly. Since more checks occur under a DevOps methodology, that means your teams will be more likely to discover bugs or issues with a software product before launch.

    Furthermore, this allows your team to constantly make small changes to improve code or repair bugs immediately rather than waiting for them to lead to long-term issues later down the road. This is beneficial since it will help you:

    • Crush bugs before your clients and customers see them
    • Fix bugs before they spiral out of control by deploying patches through the cloud
    • Avoid putting off or delaying software launches
    • And more

    More broadly, DevOps methodologies let you produce smaller releases and smaller changes. Since every code change has to be run through automated testing processes before getting to production, bug fixing is both faster and rarer. 

    More Client Satisfaction

    Lastlty, and perhaps most importantly, DevOps can help your organization produce greater and more consistent client satisfaction overall. After all, the primary goal for any programming or software methodology is to make sure that clients or end-users of software have excellent experiences and don’t have any complaints.

    This is even more important in the modern day when you have to compete against other software development organizations all the time. If you want your organization to be efficient, agile, and organized, DevOps is the way to go.

    DevOps should produce software with:

    • Fewer bugs or other issues
    • More manageable software updates and releases
    • A more integrated team supporting its processes
    • And more

    All of this will contribute to a better initial and long-term experience for clients or end users. In addition, DevOps allows your team to deliver innovative solutions or code changes quickly and easily, allowing your brand overall to improve customer experiences as time goes on.

    In other words, DevOps lets you evolve your product along with the desires of your customers.

    Conclusion

    As you can see, DevOps practices and methodologies are beneficial in more ways than one. Once you adopt DevOps for your organization, you could see improved efficiency, more continuous delivery of online or software-based services and other advantages. Both you and your clients will benefit, so start adopting DevOps across your company today.

  • Latest DORA Report From Google Surfaces Raft of DevOps Challenges

    Latest DORA Report From Google Surfaces Raft of DevOps Challenges

    The annual Accelerate State of DevOps 2022 report published today by the DevOps Research and Assessment (DORA) team at Google found the percentage of high performers is at a four-year low, with the percentage of low performers rising dramatically from 7% in 2021 to 19% in 2022.

    Based on a survey of 1,350 DevOps professionals, the report evaluated organizations based on the five DORA metrics: Deployment frequency, lead time for changes, time to restore service, change failure rate and operational performance. The DORA team also identified clusters of DevOps teams ranging from “starters” to “flowing” based on their overall maturity. Only 17% of respondents achieved a ‘flow’ state defined by high reliability, high stability and high throughput characteristics.

    The DORA survey sample shifted this year to include more respondents that are earlier in their careers than in previous reports. However, Claire Peters, DORA research lead at Google, said that while there are a lot of factors that impact those metrics, the current hypothesis is that the COVID-19 pandemic has taken a toll on DevOps productivity as more DevOps professionals continue to work remotely.

    The report noted a marked shift in deployment targets requiring new skills, with 54% of respondents now working with container artifacts.

    Overall, the report finds software delivery performance is beneficial to organizational performance when operational performance is also high. The challenge is the number of organizations that have achieved high operational performance is relatively small. In fact, the report also noted that site reliability engineering (SRE) practices had a negative impact on software delivery performance until an organization achieved a high level of SRE maturity.

    The report also concluded that organizations that built software on and for the cloud tended to have 1.4 times higher organizational performance than those that didn’t. The percentage of respondents using public clouds is 76%, up from 56% in 2021, while the number of respondents not using a cloud stands at 10.5%. Usage of multiple public clouds is at 26%, while 35% reported using a private cloud.

    Less clear is the impact on DevOps teams of shifting application security left. The report suggested the biggest challenge organizations face when it comes to achieving application security have more to do with cultural issues than any technical shortcomings. The report notes that organizations that focus on accelerating software delivery without implementing meaningful DevSecOps best practices find themselves in a vicious counterproductive cycle that results in applications being successfully deployed in production environments less often.

    Peters noted that there is greater developer fatigue because organizations attempt to address security issues either just before an application is deployed or they remediate applications after they are deployed. Organizations that have low levels of security practices are 1.4 times more likely to experience developer burnout.

    The DORA team used both the supply-chain levels for secure artifacts (SLSA) framework defined by Google and the Secure Software Development Framework (SSDF) defined by the National Institute of Standards (NIST) to evaluate organizations. The most widely-adopted practice is application security scanning within a continuous integration/continuous delivery (CI/CD) system, with 63% of respondents reporting these tools are “very” or “completely” established. Preserving code history and using build scripts are also highly established, the report finds.

    In general, Peters said the report suggested the biggest predictor of application security success was whether an organization had a high-trust, low-blame culture focused on performance. Organizations that have these cultures tend to have higher organizational performance. Similarly, organizations with teams that felt supported through funding and leadership sponsorships tended to have higher organizational performance, the report noted. In addition, team stability and positive perceptions about one’s team also tended to lead to higher levels of organizational performance. Lastly, companies that offer flexible work arrangements tended to see higher levels of organizational performance.

    Each organization, as always, will implement DevOps best practices in ways that best fit its internal culture. However, the latest DORA report makes it clear that the more empowered a DevOps team is the more proficient they tend to become.

  • Using Internal Wikis for Web Development Projects

    Using Internal Wikis for Web Development Projects

    A team-based web development project is always a complex endeavor. It involves different developers with varying levels of experience, different fields of expertise, milestones to accomplish and a timeline to achieve.

    To facilitate the sharing of information, it’s not always enough to use project management tools like Asana or Jira. Sometimes, a wiki may be needed to help distribute knowledge and best practices to everyone working on the project.

    In this guide, we discuss the practicality of using wiki tools for information sharing among web devs.

    What is a Wiki?

    A wiki is a program that enables users to collaborate in the creation and population of the content for a website. The word comes from the “wikiwiki,” which is Hawaiian for “fast.” In other words, a wiki is an app that allows for crowdsourced content to create pages of information.

    In addition to wiki pages, Web 2.0 tools allow users to connect and share information via rich media such as RSS, OpenSocial and OpenID. Another use for wiki tools is to share creative content such as photography and design concepts. A very simple way of sharing web pages on the wiki is to add a share icon at the top of the page. Simply add the share icon to a wiki page.

    The Benefits of Wikis

    Wikis bring a number of benefits to web dev teams, such as:

    Knowledge Sharing

    Since people working on the project have different levels of expertise and experience, the wiki allows subject matter experts to contribute information based on their specialization. This valuable knowledge can be accessed by others who need such information and dispels the formation of “information silos” that usually impede teams working in isolation from each other.

    Searchable

    The information stored in a wiki is categorized and organized in hierarchical and logical structures. It allows users to easily search for information based on topic, field or category, and learn what they need in an instant. This improves productivity and minimizes the need to chase other colleagues down in the search for data.

    Single Source of Truth

    By acting as a central repository of information, all data gets vetted before making it into the wiki. This makes the stored information verified and accurate and the wiki acts as the single source of truth for the whole team.

    Easy Updates

    The wiki allows contributors to update information easily and conveniently. As such, all references are up-to-date–a critical factor for any web dev project.

    Wikis and Web Development

    Wikis have the potential to make it easier to share knowledge with stakeholders as well as spread the expertise of a motivated development team, leading to better management and accountability. 

    Many wikis are publicly funded in different ways. For instance, several open source wikis exist, such as BikiWiki, ObjectiveWiki, GrowWiki and PDFLabs wiki, but we can see a few web-based initiatives in this space as well. These include Virgil Technology wiki and KnowledgeVerify.

    Microsoft’s SharePoint platform is arguably one of the best solutions for online collaboration on web-based projects. Because SharePoint is integrated with almost all major applications (Windows, Word, Excel, PowerPoint, etc.), users can create shared webpages based on SharePoint site templates and share these with their colleagues. While it’s true that SharePoint cannot solve all the problems related to information sharing and preservation, it provides a great starting point for finding common ground on project development.

    The Advantage of Wikis Over Other Collaborative Tools

    While project management tools usually incorporate collaborative functions, they are not as full-featured as a wiki is when it comes to knowledge sharing. The wiki is notable for having the following features that other tools may lack:

    Search functionality: Wikis have full-featured search capabilities to aid in the search for information. No need to drill down tree structures and categorical hierarchies.

    Comments: Adding comments to a page is an efficient and fast way to contribute and help others.

    Content creation: You can write wiki articles using any text editor, or you can write it using the wiki syntax—it largely depends on the platform. The wiki syntax is quite similar to the HTML format. One thing that makes wikis useful is that when you share a wiki page, everyone can see the changes as they are made. So sharing works through a web link instead of having to publish to a file.

    The wiki markup is a sequence of tags that represent the structure of a page. There are two main types of wikitext; the wiki syntax and the HTML syntax. The wiki syntax comes from Wikipedia, which is a popular wiki. Both are immediately available to devs, making content creation and editing easier.

    Access control: Since wikis can change based on edits and the number of links get added to the pages, they use an access control and version management system.

    With its growing array of software options and constant framework decisions, the world of web development always needs quick, organized patches of information. Rapid creation and publishing options mean that, for an almost 20-year-old technology, wikis can still be a valuable tool for web devs today.

  • How IaC Helps Relieve Development Pain Points

    How IaC Helps Relieve Development Pain Points

    Developers spend much of their day digging into their systems’ guts, allocating storage to an application, connecting the security system to the user interface and tracking which version of the application is where in the development cycle, among other tasks.

    That’s why a new category of software has emerged, infrastructure-as-code (IaC), that promises to automate system infrastructure provisioning and integration. It frees up time so developers can focus more on frontend solutions rather than backend configuration management. First, though, let’s find out what IaC is and how it helps your organization.

    What is Infrastructure-as-Code (IaC)?

    IaC reduces system infrastructure creation and configuration time through the use of sets of tools, protocols, languages and processes. In conventional data center system management, each configuration entry and change has historically required manual action. Now, technology teams can manage everything in an intelligent, automated manner. 

    With IaC, infrastructure configuration management data is stored within standardized files. The tools monitor and maintain the state of the infrastructure and ensure that the right resources are available whenever an application runs. This saves DevOps teams from excessive manual effort. In essence, large-scale configuration and management become dramatically simplified.

    Development Pain Points 

    Currently, development is a cumbersome process because friction arises in many places. A great deal of progress has been made in speeding up the front end of application development—building the feature set. Still, the process slows down on the back end when the software components are tied to the computer infrastructure. 

    Historically, software was deployed as one large, monolithic block of code. Updates were tedious to make because all of the application’s code had to run, even if it wasn’t involved in the update or bug fix. The advent of containers and microservices enabled developers to design applications that are modular in nature and therefore easier to update, add to or debug.

    However, the application still has to be tied into the existing compute infrastructure. Cloud solutions—like AWS, Google Cloud Platform or Microsoft Azure, for instance—provide companies with quick access to large volumes of computing processing power. But that application software must be told how to access the network, present security information, allocate storage and run code on central servers.

    Because of this, developers spend a lot of time building and maintaining infrastructure-as-code. To do so, they use languages like Python and solutions such as Chef and GitHub. They want to use automation to simplify and accelerate the process, but here, again, they encounter some roadblocks.

    Workflow Bottlenecks

    As applications become larger and components become smaller, developers find themselves mixing and matching software from a wide variety of places. Tracking what’s where in the process is a frequent challenge. Current workflows are often non-intuitive and rely heavily on pull requests. Some solutions try to address the problem with multiple workspaces, but the end result is fragile and nondeterministic code.

    Without mapping of projects to branches or tags, someone who comments on an approved pull request can push unapproved code to production. In today’s fast-paced DevOps work environment, an approval meant for a short-lived test run becomes the current release, creating a ripple effect of unintended consequences that create confusion and defective code, slowing development—often substantially.

    Access Control

    Most tools do not offer access control models. Developers can track a single repository and a single Terraform project, for example, but as the number of repositories and projects grows, ensuring that proper access control features are in place becomes more daunting. 

    Workspace Challenges

    Legacy waterfall and static development projects allowed IT teams to set their system infrastructure up once and forget about it. But in a dynamic environment, microservices come and go in the blink of an eye. New environments proliferate and product teams must continually configure their own workspaces, which eats up time and resources.

    Drift Detection

    Generic IaC platforms don’t provide mechanisms to detect if the infrastructure is drifting. Because so much configuration is done at runtime, differences arise between the desired and the actual state of the infrastructure.

    Drift has many causes, such as developer or machine script contingencies or the lack of system resources. Too much drift results in unstable applications. Catching such problems early in the development cycle is more efficient than trying to fix a production system. But needed visibility is often lacking, and shortcomings become clear only when the system is fully in use.

    Resource Visualization

    Given today’s dynamic environment, developers need clear visibility. They must be able to closely examine what happens as their job runs. Though they offer many advantages, CI/CD platforms deliver little insight into resource usage from a real-time or historical perspective.

    So, whenever performance problems arise, these platforms offer little insight into what the source of the problem is or how to fix it. Consequently, developers’ attention shifts from application enhancements to troubleshooting.

    Lack of Reusability

    Legacy infrastructure failed to let teams reuse tried-and-true system images across multiple environments. To address this problem, teams often create a new image for each version of each application, slowing development time. 

    High Prices

    Setting up each IT environment manually requires time and manpower, which raises costs. Companies must have dedicated teams of engineers responsible for creating the infrastructure. But they also need supervisors and data center resources, which ultimately boost technology expenses. IaC tools centrally manage the process and create the right environment. That way, organizations pay only for system resources that they truly need.

    How Does IaC Improve the Business? 

    Legacy IT practices are expensive, slow and inconsistent because they rely heavily on manual input. Infrastructure-as-code automates much of the infrastructure management process, which delivers a range of benefits.

    Speed 

    With IaC, provisioning and management are lightyears faster and more efficient than with a manual system. The environment’s infrastructure is defined in code. That code-based infrastructure significantly accelerates each phase of the software development and delivery cycle. Consequently, DevOps teams deliver applications faster and at scale while improving software quality.

    Consistency

    IaC deploys consistent configurations constantly and with no discrepancies. Because of this, it enables fast delivery of consistent infrastructure and environments. This reduces errors and overhead while boosting productivity.

    Eliminating Management Overhead

    Infrastructure automation helps to reduce the number of people with hands on the routing parts of the software development process. That’s because human resources aren’t needed in the management of networking and storage. Companies free up personnel to work on more strategic initiatives.

    Reducing Risks and Errors

    IaC helps to reduce risks and avoid human errors. It also protects against runtime issues and security weaknesses caused by missing dependencies or configuration drift.

    Visibility

    Developers version IaC configuration files the same way they do any other source code file. This gives them complete traceability of any changes. In this way, IaC ensures efficient, exceptionally transparent workflows and speeds up the development process.

    Finding an IaC Solution 

    Maintaining legacy infrastructure was a time-consuming, complex process. IaC is emerging as a solution that alleviates much of the stress and pain that developer teams feel daily. Now, they can speed up the deployment and connection of system resources to applications. Developers can become more efficient and enable the company to respond to business demands in a faster, more reliable and more cost-effective manner. The development process no longer slows down the business. 

  • Why Object Storage is Best for Cloud-Native Apps

    Why Object Storage is Best for Cloud-Native Apps

    A crucial question that plagues cloud application developers is, “What kind of storage should we use for our app?” Unlike other choices like compute runtimes—Lambda/serverless, containers or virtual machines—data storage choice is highly sticky and makes future application improvements and migrations much harder.

    All three hyperscalers have storage services that present block, file and object-based data access. Each of these storage services are mature and offer different advantages, making the choice even harder. Though block and file-based storage has existed for multiple decades, in this article we will illustrate some key differentiators that should make object storage your default storage choice for new applications written in the cloud.

    Storage Type/Cloud Provider Google Cloud Amazon Web Services Microsoft Azure
    Block Persistent Disk Elastic Block Storage Disk Storage
    File Filestore Elastic File System Files
    Object Cloud Storage Simple Storage Service (S3) Blob Storage

    Easy Scaling

    Scalability is an important requirement for most cloud applications. It is expected that horizontally increasing the amount of compute power available to an application increases its ability to process requests, users, etc. to handle peak workload. Most cloud providers also make it easy to scale up compute resources to meet peak demand. As compute resources are scaled,
    block and file-based storage need to be mounted/attached to the new compute instances.

    However, a cursory search will show that these operations can fail or even hang indefinitely for multiple reasons. They also are often hard to debug. The other issue with using file and block storage solutions is that teardown of the compute instance may fail or hang for the same reasons. These issues immediately negate the application’s ability to scale freely as required. This is, however, not an issue with object-based storage, since there is no mount step involved. Your object storage is instantly accessible to the newly-created compute instances.

    Sharing and Consistency

    Data sharing and consistency are where object storage really shines compared to other storage types. In both block and file-based data storage, one instance of an application can end up seeing partial data written by another instance. Application developers end up having to use persistent locks to get around this issue. However, such schemes come with their own sets of challenges: Performance, correctness, etc. Persistent locks end up making an application severely complicated; I have seen even experienced storage engineers make mistakes while using persistent locks. Object storage avoids this problem by not exposing partially-written objects or objects actively being written. Also, note that objects are typically immutable, so once written they can only be overwritten as a whole and not in parts. This means updating data requires expensive read-modify-write cycles. However, most cloud providers help avoid these additional reads via special APIs that can create an object from portions of an existing object like GCS compose, Azure’s put page blob and AWS multipart upload.

    Data Protection

    Errors are bound to happen during application development or rollouts. These errors can end up impacting critical data and potentially disrupt normal application operations. This is why it is essential to have some sort of backup/snapshots configured on the storage that you use.

    Though most storage services have some form of backup/snapshot mechanism, most don’t make it very easy to configure or restore from them (that is, both require multiple steps or the involvement of a cloud administrator). All cloud object services support native data/object versioning capabilities which are extremely easy to enable. So, basically anytime an application updates and/or deletes, the object storage service preserves the older copy of the data. In case an older copy of the data needs to be restored, you can just read the old version and write it as the new object. The careful reader might see that if an application writes/deletes data often, there may be a lot of older versions of the data left behind. One might think these would be hard to identify and remove when not needed. However, all cloud providers support policy-based data life cycle management (see next section) so you can set up policies to delete unnecessary copies. Note that object versioning also provides an excellent defense against ransomware attacks.

    Policy-Based Data Life Cycle Management

    The amount of data being generated by applications is only going to keep increasing with each passing year. This is the reason all the cloud providers support policy-based data life cycle management for their object storage services. Even if you don’t expect to use more than a few gigabytes of data, policy-based life cycle management can help you keep your storage costs in
    check and can help reduce your code complexity around handling application crashes. Policy-based life cycle management especially comes in handy when you or your cloud admin decide to enable features like object versioning and object holds for data protection and compliance reasons. These policies are very simple to set up and can easily be customized to the needs of
    the individual organizations/applications/developers requirements.

    Conclusion

    As one can see from the above, object storage services have been built to enable the development of simple and scalable applications. So, if you are writing a new application from scratch, choose object-based storage to keep your applications simple and easy to maintain.

  • How to Go Multi-Cloud: A Simple Three-Step Approach

    How to Go Multi-Cloud: A Simple Three-Step Approach

    Odds are your business already uses cloud technology for automation, cybersecurity, IT infrastructure updates and other purposes. But you don’t have to stick to a single cloud server or provider. In fact, you can take advantage of multi-cloud strategies for your organization and reap the benefits for years to come.

    That said, multi-cloud adoption and optimization can be tricky, especially if you don’t have a plan in mind from the get-go. Today, let’s break down a simplistic yet effective three-step approach to go multi-cloud without running into major problems.

    Step One: Map Your Cloud Zoning Policy

    Your first major step should be to map out your cloud zoning policy and plan. In a nutshell, the cloud zoning choices you make can impact your commitments, costs, and even the eventual functionality of the multi-cloud setup.

    By mapping out your clouds, you also map out which processes and applications will run on each individual cloud server or provider. In essence, you decide what gets locked into one cloud, what data has to be ported between clouds and what applications must run on multiple clouds simultaneously.

    Need an example? A cloud zoning policy might cover whether you keep your web surfing or data analytics on separate cloud providers or on the same cloud servers. 

    You should map your cloud zoning policy regardless of whether you do the setup or hire a service. In the latter case, offering a read-to-go zoning map will make the service’s job easier and minimize the possibility of mistakes and/or hiccups.

    How to Determine Optimal Cloud Zoning

    Naturally, figuring out how to optimize cloud zoning can be difficult. The best way to do this is to determine your special focus areas. Alternatively, consider how you want your multi-cloud strategy to best benefit your organization.

    Say that you want to guarantee 100% uptime for your customers or visitors, even if your service goes down or if you experience a data breach. In this case, you can set up your cloud zoning strategy to balance the data load across multiple clouds at the same time.

    Or say that you want to make sure your users have global availability 24/7/365. In that case, you can set your cloud zoning policies to ensure that users can access your data or websites from anywhere around the globe at any point.

    Essentially, figure out what matters most to your organization–and what you want the most from multi-cloud optimization–and zone your cloud applications and policies accordingly.

    Step Two: Architect the Multi-Cloud Environment

    The next major step is to architect your multi-cloud environment. This involves looking at the high-level design of the environment and creating a rock-solid foundation for multi-cloud servers.

    At this stage, you should have at least some idea of how your business will grow and how the multi-cloud environment will assist with its scalability and resource needs. You need to know:

    • Where your data science and machine learning applications need to be
    • Where your product application serves from
    • Where your data warehousing takes place
    • Where cloud security is run from
    • How each of those functions grows alongside the others

    In the architecture phase of a multi-cloud setup, you need to figure out which projects and apps are so-called “cloud agnostic.” Cloud agnostic projects and applications don’t have to be portable; because of this, they can lean on managed services or proprietary IT infrastructure from your organization.

    How to Set Up an Ideal Multi-Cloud Environment

    To reap the most benefits out of a multi-cloud environment, you should adopt a containerized and flexible approach. Not only is this cost advantageous, it also allows you to set up your multi-cloud environment with as much versatility as possible.

    If you architect or plan your multi-cloud environment so it is containerized and flexible, you can work with practically any infrastructure-as-a-service (IaaS) provider. Therefore, you can transition to different cloud hosts or service providers whenever necessary according to your budget or other factors.

    To do this, be sure to perform heavy forecasting. You need to know how much data storage your computing will require, the database utilization your organization will need, the number of computer nodes you’ll likely require and so on.

    As a side bonus, containerization in your multi-cloud setup means that if one server or process goes down, the others are less likely to fail from a cascade effect as well.

    Step Three: Prep for Contracts and Forecast Costs

    The last step in going multi-cloud for your organization is handling the financial aspect of the process. You need to prepare for contracts and commitments alongside forecasting costs.

    Forecasting is critical in this phase because you’ll prepare for contracts and select different cloud services. Because of this, you need to understand how flexible your budget is relative to your infrastructure requirements.

    Specifically, you’ll need to match the costs to every multi-cloud forecast and build your overall resource and money consumption budget. Basically, you need to know:

    • How much you’ll likely spend on multi-cloud processing and services
    • Whether you need certain features, such as website monitoring tools like Visualping
    • Whether your budget can take that forecasted strain

    If the answer to the third question is “no,” you may need to go with a more affordable service or adjust your multi-cloud environment architecture and zoning policies. By forecasting costs ahead of time, you won’t run into a disaster scenario where you already have your multi-caught environment up and running but can’t pay for it, forcing you to scramble as a result.

    Minimize Commitment Risk

    Luckily, there are ways to minimize commitment risk and avoid budgetary disasters. For example, you can use commitment buy-back guarantees, or you can use flexible commitment options like that from AWS. These include computing savings plans, which consume cloud resources in any region and which result in very low savings rates.

    Of course, you can and should also practice very careful budgeting and accounting. Once you ensure that your commitment costs and savings are attributed to the right services, server resources, applications, etc., you’ll have a better idea of how much money and other resources you really need and avoid over-committing to a provider that is too expensive.

    Then you can further avoid commitment risk when planning your migrations of applications between different vendors carefully. Budgetary costs can skyrocket if migrating applications and data between vendors take longer or result in unexpected complications. Therefore, you should make sure that your migrations go quickly and easily or that a cloud service provider offers assistance during this phase (possibly as part of a deal to get you to sign with them in the first place).

    Wrapping Up

    As you can see, you can transition your organization to multi-cloud in a matter of months. But even if you follow the above steps perfectly, remember that you won’t optimize your commitments, performance and costs up to 100%. Still, you can prep your organization for long-term success and multi-cloud benefits with the right preparation and planning.

    With the right cloud services provider, you’ll gain additional assistance and support throughout this process and be able to take advantage of the extra resources from a multi-cloud setup quickly and easily. 

  • 8 Web Development Trends to Follow

    8 Web Development Trends to Follow

    Since the inception of the internet in 1983, many web development tools have been introduced to simplify complex processes that would otherwise take months to finish and cost companies a great deal of money.

    According to internet live statistics, over 1.5 billion websites and more than five billion active daily internet users visit multiple sites around the clock. That number is expected to grow as businesses (and website owners) offer personalized experiences to users, make their websites more user-friendly and introduce navigation that visitors prefer.

    Website development has changed and is still evolving quickly. As a website owner, it’s imperative to watch out for new trends that are being introduced in the industry. Neglecting to adopt current trends might affect your website’s functionality, user experience and network. You risk falling behind your rivals and losing visitors to websites with superior user experiences and network scalability.

    The best way to maintain competitiveness is to make sure your website is consistently updated, fresh and that it follows current trends. Here are eight to watch out for.

    Progressive Web Apps (PWAs)

    PWAs speed up website loading times and enable offline functionality in multiple applications. PWAs have already been used by businesses like Starbucks, Uber, Pinterest and Twitter to improve user experience.

    It is crucial to transform web apps into PWAs, given the increased shift toward smartphones and tablets for various online functions. PWAs offer a superior user experience, increased engagement and conversion rates and lower development costs.

    Motion UI

    Motion UI is used to create fully responsive site designs. Motion UI enables developers to produce motion in a native app environment, and with a built-in motion, it can be used for any design project. A website needs to be appealing and offer the information a user seeks. Your target audience is more likely to notice websites that look good.

    Motion UI is easy to implement as the developer doesn’t need to be an expert in JavaScript. It also assists people in finding the precise information they need and improves the effectiveness of site design.

    Privacy Center

    Privacy is a core component of ensuring your customers have a safe user experience when navigating your website. Privacy Center is an intuitive way of cataloging your privacy policy and notices, terms of service, cookie policy, refund policy, data subject requests and more on a single page.

    Privacy Center enables users to obtain information regarding a company’s data activities from a single source without having to navigate multiple pages and scroll through endless paragraphs to identify the information they need.

    Privacy Center is a growing trend for web developers as data privacy laws impose strict obligations on companies, necessitating the need to implement intuitive privacy centers that address all concerns of users.

    Dark Mode

    Although dark mode was first introduced in 2016, it wasn’t until 2020 and 2021 that it gained popularity as a standard practice in web building. Essentially, dark mode refers to a site’s color scheme. In other words, the website has a darker background with light-colored text and other UI elements.

    Dark mode typically lessens eye strain, especially in dim lighting. When dark mode is used instead of light mode on a mobile device, it uses less battery. People with light sensitivity or vision impairments have also found it to be beneficial.

    Accelerated Mobile Pages (AMP)

    Accelerated mobile pages, better known as AMP, is an initiative that resulted from Google and Twitter working together to provide quicker mobile pages. Pages that are AMP-optimized load quicker, thus ranking better than pages that take more time to load. Compared to non-AMP pages, which may take up to 22 seconds to load, AMP pages do so in roughly two seconds.

    In web development, AMP is a simple search engine optimization method that reduces bounce rates, adapts to any browser and doesn’t need sitemaps to be discovered by search engines.

    AI Chatbots

    AI chatbots are intuitive, enabling businesses to operate more quickly over voice or text chats while enhancing the consumer experience. The technology provides a more human-like experience to visitors with the help of machine learning (ML) and Natural Language Processing (NLP) that understand the user’s intent and responds accordingly. Many well-known enterprises already use AI chatbots to communicate with their clients.

    Industry experts predict that AI chatbots or self-learning bots are the way of the future, and organizations can save money by using them instead of human customer support representatives, especially for simple queries and FAQs. AI chatbots are a long-term investment as they process orders, respond to users’ questions, connect them with the relevant department and quickly resolve any complaints, resulting in an improved user experience.

    Voice Search Optimization

    The practice of optimizing web pages to show up in voice searches is known as voice search optimization. Voice assistants and the internet of things (IoT) have helped voice recognition devices become increasingly widespread.

    Google launched voice search in 2012. Since then, the market for voice search tools—such as virtual assistants like Alexa and Siri—has seen exceptional growth. The trend is only expected to grow since virtual assistants are not currently being integrated into many internet-enabled devices.

    By 2023, eight billion digital voice assistants are predicted to be in use worldwide. Due to this enormous expansion, voice search optimization will become indispensable among the newest web development technologies.

    Push Notifications

    When users browse, push notifications—clickable pop-ups—appear before them. Companies employ this technology as a speedy route for communicating information, such as promotions and announcements. Push notifications can be integrated on any device, including laptops, cellphones and tablets.

    Push notifications are an effective tool that significantly improves users’ experience, drives visitors to your website, improves click rates, aids in grabbing users’ attention and improves conversion rates. Web applications from internet behemoths like Facebook and Google already use the technology.

    Conclusion

    Though it has been around for decades, web development continues to innovate and improve as organizations strive to influence the future delivery of web experiences. To give your users the best experience, raise the search rating of your website and reach new heights, it is crucial to keep up with these trends.

  • Understanding the Importance of Developer Experience

    Understanding the Importance of Developer Experience

    If you’re creating a developer tool, you’re bound to run into this dilemma—you know the inner workings of it really well, but others don’t. And without solid documentation and samples to follow, it can be challenging for another person to get started. Friction with the tools we use can contribute to burnout, inhibit creativity and slow down innovation.

    Developer experience (DX) is becoming integral for any software company to consider. I recently met with Christine Spang, CTO and co-founder of Nylas, to consider the benefits of investing in developer experience. Below, we’ll take a look at what exactly DX is and consider some best practices for implementing it.

    What is Developer Experience?

    Developer experience (DX) is similar to user experience but for developer-facing tools. DX considers the developer’s journey while developing with a certain framework, language or platform. “Developer experience is the amount of friction a developer experiences between having clarity on what they want to implement and getting to the point where you have created that thing,” said Spang.

    For example, consider integrating with an API to solve a common use case like payments integration. There are many steps involved here, from reading the reference documentation to getting an API key, testing calls and understanding how the service responds. After developers initially integrate the API into their application, they may also have to make continual updates as the service versions. Throughout this journey, DX can be thought of as “how hard it is to figure out how to translate from idea to output,” said Spang.

    It’s also important to note that DX isn’t only relegated to public-facing platforms. Having a quality developer experience is just as crucial for internal software. The urgency to improve internal developer experience is increasing with the surge of APIs being developed, especially since the majority of them (58%) are private APIs, according to Postman’s 2022 State of API Report. Depending on the size of a company, internal DX can encompass many areas.

    Best Practices for Investing in Developer Experience

    So, what are some methods to improve developer experience across the board? Well, having up-to-date documentation, code samples, better examples and standardized documentation rank high as positive developer experience traits. Spang also shared some helpful best practices to improve DX:

    Provide scaffolding for the most common cases. Measure patterns around the kind of things people are building with the platform and offer scaffolding to support the common use cases. This might equate to a getting started guide for a common scenario.

    Offer sample code libraries. It’s a lot easier to edit code than write it from scratch. With that in mind, create pre-baked environments where developers can play around. Offering working apps, use case templates and glue code can be a practical means to help developers get going more seamlessly.

    Start with the reference manual. Walkthroughs and sample code should never replace a complete reference manual. It’s essential to have up-to-date documentation to cater to advanced users from the get-go. From here, you can generate Postman Collections or interactive sandboxes built around the reference specification.

    Measure DX success and iterate. One way to monitor developer experience metrics is to record the onboarding flow and measure conversion rates. Where APIs are concerned, this can be tracked by asking how many people get through to making calls? What is the mean time it takes to make the first call? Knowing such metrics can inform how effective your tool’s self-service features are.

    One point that’s important for DX is walking the fine line between too much custom work and focusing on the core project. On that note, Spang recommended “making sure whatever you’re building maps to the overall vision of the company.” In essence, if you’re not a consulting shop but a product company, you should stay true to that objective.

    “You want to make the path for what people commonly want to do very easy,” said Spang. “Yet, you don’t want advanced users to feel constrained by the platform.”

    Examples of Quality Developer Experiences

    For those creating developer-facing services, it’s helpful to have a framework to model. So, what are some examples of quality developer experiences?

    Well, top public APIs are great examples of where the bar is set for developer expectations these days, said Spang—services like Twilio or Stripe demonstrate relatively seamless developer journeys. Spang also pointed to companies with a strong DevOps and CI/CD background, like Etsy, who have for years invested in usable backend infrastructure that accelerates internal development.

    For other sources of quality developer experience, consider the high-ranking developer-favorite technologies from the latest 2022 Stack Overflow survey. Engineers love working with technologies such as PostgreSQL, AWS, Phoneix and Docker. The newer, trending languages tend to be increasingly usable, too. For example, 86% of developers said they love working with Rust while 76.65% dread working with Objective-C.

    The Overall Benefits of DX

    An investment into developer experience can help improve agility and developer satisfaction, said Spang. For one, an easier path for development increases the velocity in how you ship and evolve projects over time. Secondly, developer experience equates to less burnout and less turnover, both of which can have real business impacts.

    The software development industry is growing like wildfire, bringing in waves of entry-level developers each year. Interestingly, the average experience level is decreasing, increasing the need for more abstracted tools and toolkits, said Spang. In this environment, developer experience undoubtedly shines as a competitive advantage.

    So, if you’re creating developer-facing tools, consider the experience others will have when using them. Increasing developer experience may just be a defining factor in the project’s success and the long-term happiness of your developer community.

  • Free Dev Tools! But What’s the Catch?

    Free Dev Tools! But What’s the Catch?

    Software companies, especially young startups, are always in a development race – by definition, they are trying to maximize achievements and minimize their burn rate. That means development teams naturally face an internal tug-of-war. On one hand, they seek to use the newest dev tools that the market can offer, targeting their applications to become better (more secure, more efficient and compliant with the latest standards). On the other hand, they cannot spend money on such tools since they need to save every penny. With the current economic climate, many new investments are being delayed or, at minimum, double-checked. 

    To appeal to developers, many vendors and software development tool companies offer freemium programs. Some are driven by the spirit and the goodwill of open source and community; others are business-to-developer (B2D) companies relying on the product-led growth (PLG) mode. If developers see value in the free tools, they are more likely to become paying customers later on to get access to more features.

    Here, we’ll review the common parameters of popular free developer tools and distinguish their services between the free tier (aka the community tier), the entry-level paid tier and other paid program offerings. We’ll look at tools for observability, logging, vulnerability scanning, compliance, authentication and VPNs.

    1. Volume Threshold

    Logs are considered to be one of the three pillars of observability and are the bread and butter of troubleshooting and debugging. The more code lines you have in your product, the more loglines you collect, store and aggregate. Logs accumulation can quickly get out of hand and become very heavy on the budget. One logs aggregation vendor, Sumologic, provides a freemium offer that allows log collection up to one gigabyte per day. If you need more volume, you can move to their paid tier that allows for higher volumes or pay more for no limits at all.

    2. Transactions Threshold 

    Transactions and tests are probably the most imperative features of a freemium offer. It involves the core offering with a quantity limitation, giving you a chance to try the product through practical use, but you’ll probably have to move up quickly into the first paid tier. Snyk.io, for example, will help you scan your open source software for flaws alongside container vulnerabilities as early as code creation, with up to 200 open source tests and 100 container tests per month.

    3. Certified: Security and Compliance 

    It’s one thing to play with, say, a free AutoCAD seat that doesn’t involve sensitive data and another thing entirely to draft the next-generation design that must not leak to your competitors. Security and compliance certification is often included in the freemium tiers; more detailed reports and analysis of security and compliance are for the paying tiers only.

    4. Availability and SLA Support 

    Having a free tool is great–but if this tool is bound to a proprietary service, then you should probably demand these tools meet the same standards and SLAs that you are offering your customers. Observability platform Rookout offers 24/7 support and dedicated account managers and tools for enterprise customers in all tiers.

    5. Legal Aspects 

    One key aspect of free tiers is the legal aspect of using the tool. The dev tool may interact with sensitive data, not only in your own dev environment but also with your customers’ environments. Your customers may require your dev operations to meet specific criteria, making the free tier a potential legal issue. For example, if you use the free tier of JFrog to manage your supply chain, you won’t be able to use Artifactory to publish data to third parties; should you want to do that, you will have to move to one of the paid commercial programs.

    6. Usage Threshold

    Some free tools operate based on a usage model—you are entitled to a free tier until a certain amount of users or actions is reached. Auth0, for example, a user authentication solution (now part of Okta), provides their service free of charge for up to 7,000 users (generous!) but should you grow beyond that, you’ll need to graduate to a paid tier and be charged according to your monthly usage.

    7. Speed Threshold

    Some free and freemium offerings are tempered based on connectivity speed, bandwidth and even VPN. Today, you can even get a secure VPN for free, but only to a specific threshold. For example, ProtonVPN will provide you with a free VPN at a medium speed, if you move to the highest speed VPN, you’ll need to move to a paid tier.

    In most cases, the freemium tier will limit a dev tool’s usage according to one or a few main characteristics but will allow you to perform the basic actions and enjoy the essence of the tool. Some parameters may be trivial, like volume of tests, while others require developers and DevOps teams to carefully monitor usage. There’s a lot of value in free and freemium dev tools—but make sure you read the fine print.

  • Time-Series Database Basics

    Time-Series Database Basics

    There’s been a lot of buzz about time-series data for the past few years. No matter what you’re monitoring—financial data, server performance, social media activity or something else entirely—time-series data can give you valuable insights into trends and patterns.

    But what exactly is a time-series database, and why do you need one? This article will look closely at time-series databases and how they can help you make sense of your data.

    What is a Time-Series Database?

    A time-series database (TSDB) is a database management system optimized for storing and querying data that changes over time. Time-series data is often used in monitoring applications where it’s important to quickly retrieve information about a system’s current state and trends and patterns over time.

    In most definitions, time-series data, often referred to as time-stamped data, is a sequence of values indexed in time order. Time stamping refers to data collected at various times, where each value is time stamped. These data points are usually gathered from the same source and are used to measure progress over time.

    Important Notes:

    You can use relational or NoSQL databases to crunch time-series data, but purpose-built time-series databases are tailored to exploit the unique features of time-series data. This implies that time-series databases ingest at a faster rate, query more quickly and compress data more efficiently. Furthermore, time-series databases include special analytical capabilities and management features that are not found in most relational or NoSQL databases.

    Some Advantages

    This list is not exhaustive, but here are some of the advantages that you might get from using a time-series database:

    1.) Time-series databases can handle high-velocity data very well.

    2.) Time-series databases are purpose-built for storing time-series data, making them more efficient in storage and querying.

    3.) Time-series databases often have built-in analytics and management features designed specifically for time-series data.

    4.) Many time-series databases are open source, which means they’re free to use.

    Some Disadvantages

    There are also some disadvantages that you should be aware of before using a time-series database:

    1.) Time-series databases are often more complex to set up and manage than relational or NoSQL databases.

    2.) There are relatively few time-series databases to choose from, so you might not have as much flexibility in choosing a platform that meets your specific needs.

    3.) Time-series data can be very large, so you’ll need enough storage capacity to accommodate your data.

    What Are the Characteristics of Time-Series Data?

    There are several characteristics of time-series data that make it unique and require special handling. From a database standpoint, the most essential ones are as follows:

    1. Timestamp: Every data point has its timestamp. The timestamp is crucial for calculating or analyzing the information.
    2. Structure: Metrics from devices or monitoring are almost always structured, unlike those produced by Internet applications. They have predetermined data types and lengths, and the structure will not alter until the device’s firmware is updated.
    3. Stream-like: Data sources, such as audio or video programs generate data at a set or constant rate. These data streams are completely unrelated to one another.
    4. Stable flow: Time-series data traffic is constant over time, and it may be calculated and predicted if enough data sources are used within a certain sampling period.
    5. Immutability: The source of this data is a time-series data store. Each data point is created only once and never updated or corrected. Time-series data, like log data, is typically append-only.

    How Is Time-Series Data Used?

    Many of you may be wondering why time-series data is so important. The answer is that it allows us to track changes over time, which can be incredibly valuable for monitoring and troubleshooting purposes.

    For example, let’s say you’re a system administrator tasked with keeping an eye on server performance. By monitoring various metrics—such as CPU usage, memory usage and network traffic—you can quickly identify when a server is starting to experience issues.

    Time-series data can also be used for predictive purposes. For example, if you notice that CPU usage spikes at certain times of day, you can use that information to plan for future capacity needs.

    Of course, time-series data isn’t just limited to server performance. It can be used for any application where it’s important to track changes over time. This includes everything from weather and financial data to social media and website analytics.

    Let’s Get Specific

    Here’s what you should know about time-series data: It’s typically used to seek insights into operations, create alerts based on real-time analysis and forecast future trends.

    The following characteristics are found in time-series data applications:

    1. High write-read ratio: Twitter and LinkedIn are internet applications with single articles that millions of people read, but raw time-series data is primarily scanned and evaluated by apps and algorithms.
    2. Retention policy: In general, time-series data is not kept permanently. Organizations have a retention policy that specifies when and how their data is destroyed.
    3. Real-time analytics and computing: Time-series data must be calculated in real-time to identify out-of-the-ordinary activity and sound alarms based on the acquired information or aggregate findings.
    4. Query scope: Time-series data is generally requested over a period or a set of data sources, and filters are used to prevent all historical information from being requested. Furthermore, all or a portion of the data sources with a filter condition are always aggregated.
    5. Trends: Single data points are typically not significant in time-series data. The emphasis is on how data evolves, such as fluctuations in the previous hour or day.

    Popular time-series solutions like TDengine or InfluxDB, for example, create more efficient processing of time-series data and greater performance than general databases by taking advantage of these qualities.

    Do Time-Series Databases Need Specialized Databases?

    We live in a modern world where data is constantly being generated at an unprecedented rate. To keep up with the demand, businesses need to be able to store and process large amounts of data quickly and efficiently. This is where specialized time-series databases come in.

    Everything is online, including meters, automobiles, lifts, assembly lines and even bicycles. And these items are sending out a never-ending stream of numbers and events that IoT and the cloud have unleashed an explosion in time-series data generation.

    With this in mind, it’s not surprising that several specialized time-series databases have been created to deal with this type of data influx.

    Time-series data sets are enormous and pose a significant problem for general database management systems, such as relational and NoSQL databases. Non-specialized databases have trouble with the following elements of time-series data:

    1. Data ingestion rate: In many time-series data scenarios, millions of data points are generated every second and must be ingested in real-time. Relational databases are not built to handle this quantity of data, and while NoSQL databases may be scaled to do so, the amount of resources required soon becomes prohibitive.
    2. Query latency: It is often the case that a time-series system must scan a massive number of data points to get an aggregate result, which might lead to sluggish performance. For example, it would take days for a basic database to compute the average response time of all Amazon.com clicks, by which time the overall conclusion may be incorrect.
    3. Storage cost: Data generated by internet-connected devices and apps is nonstop 24/7, with a single day producing as much as a terabyte of data. Because relational and NoSQL databases cannot compress this data effectively, storage costs can quickly skyrocket.

    These problems are generally linked to efficiency in processing big data sets, although there are some places where general databases frequently do not meet even the fundamental demands of time-series applications:

    1. Data life cycle management: Time-series data is generally removed in bulk, not one data point at a time, as it ages out.
    2. Roll-up: In most cases, time-series data is collected and rolled up over a set period before being stored in the new table. Raw data and rolled-up data can have distinct life cycles and retention policies.
    3. Special analytic functions: Time-series applications need more specialized features than general databases, such as time-weighted average, moving average, cumulative sum, rate of change, elapsed time for a specific state and the delta between two consecutive data points.
    4. Interpolation: The database management system must be able to interpolate data based on the adjacent data points and rules to regularize data sets when applications or algorithms require.
    5. Continuous query: Therefore, if you hear a user or customer say they want to know when their data is updated, it’s reasonable to assume they want this functionality.
    6. Session and state windows: Aggregations and analytical procedures may be performed on a session or state window, not just time—for example, consider one that only calculates average power consumption when a machine is switched on.

    With general databases, developers must write custom code to implement features specific to their data set. Different data workloads require different database solutions; one size does not fit all. For time-series data, no matter the size of your data set, a purpose-built time-series database is the best tool for the job.

    Why Are Time-Series Databases Becoming Popular?

    Two years ago, time-series databases were the most popular database type in the business, owing to its expanding number of use cases. It is especially useful if you’re executing sophisticated transactions like advertising, e-commerce, supply chain management and so on.

    However, because of the rapid expansion of the IoT, they are becoming even more popular. As more devices become internet-connected and send data—time-series, of course—to the cloud, many industries are interested in purpose-built time-series databases.

    Time-series data is proving to be an important tool, not just for decision-making and optimization but also for industrial applications. Finally, IT infrastructure has been growing rapidly, with everything from servers, containers, network devices, apps, and microservices being monitored to create massive quantities of time-series data.

    Older time-series databases, on the other hand, are often closed systems employing antiquated structures that do not scale to handle the increasing amount of data. A million time-series data points used to seem like a lot, but now millions and even billions of data points are commonplace.

    Finally, integrating old (previous) time-series solutions with popular data analysis tools like artificial intelligence and machine learning platforms is difficult, if not impossible. These legacy systems cannot be transferred to the cloud without a lot of work and their licensing terms are no longer adequate for current apps.

    Final Thoughts

    The expanding market and the constraints of previous time-series databases are making room for a new generation. These new time-series databases are built from the ground up to take advantage of the cloud, big data and AI/ML technologies.

    If your business or application deals with time-series data, you need a purpose-built time-series database. The advantages of using such a database are too great to ignore, and the disadvantages of using an older, less capable database are becoming more and more apparent.