devopsy.kinsta.cloud

Category: Cloud Management

  • AWS Delivers on Latest Graviton3 Price/Performance Promise

    AWS Delivers on Latest Graviton3 Price/Performance Promise

    Amazon Web Services (AWS) has expanded the number of virtual machines based on the latest generation of its Graviton processors to include instances that support DDR-5 memory.

    The latest Amazon EC2 instance types, dubbed M7g and R7g, that are now generally available are based on the AWS Graviton3 processors developed using an architecture created by Arm. Previously, these instances were only available as part of a technology preview program.

    Rahul Kulkarni, director of product management at AWS, said these latest offerings take advantage of DDR-5 memory to provide 25% better performance than the previous sixth generation of Graviton instances. DDR5 memory increases the amount of bandwidth available by 50%, he noted.

    Graviton processors now provide the lowest-priced instance of virtual machines in addition to the best performance and overall price/performance across the AWS portfolio, Kulkarni added.

    AWS is making a case for employing its AWS Graviton processors for general-purpose workloads as more IT teams are being tasked with reducing costs as the overall number of applications being deployed in the cloud continues to increase. In fact, all of the top Fortune 50 companies have already deployed workloads on Graviton processors, noted Kulkarni.

    While it’s not clear how many applications are being developed to run natively on Arm processors, the process of refactoring existing applications to run on Arm processors is not as intensive for most applications as it was when previously moving applications from one class of processors to another.

    In addition, Kulkarni noted AWS has committed to providing a full range of DevOps services, including a continuous integration/continuous delivery (CI/CD) platform, to help facilitate any transition to Graviton processors.

    There are, of course, multiple strategies for containing cloud costs that range from committing to consuming a specified amount of compute resources annually at discounted rates to relying more on spot instances that are available for limited amounts of time. Regardless of approach, the days when developers were allowed to invoke cloud resources at will appear to have come to an end as enterprise IT organizations become more aware of the total cost of IT. As a result, many of them are adopting financial operations (FinOps) best practices to maximize the utilization of cloud infrastructure resources.

    AWS, like most cloud service providers, gives organizations a wide range of processor options. However, it’s apparent that AWS views Arm processors in the form of Graviton to be the most efficient from both a price and performance perspective. It’s not clear how quickly organizations are embracing Graviton in the cloud given the dominance of x86-based platforms, but it’s apparent there is now a clear alternative for general-purpose workloads. If fact, the more data-intensive those workloads become, the greater the interest in more efficient processor architectures.

    Of course, x86 platforms are not going away anytime soon. But as more Arm-based processors find their way into the enterprise, DevOps workflows will only become more challenging to manage.

  • Technical Debt is a Major Threat to Innovation

    Technical Debt is a Major Threat to Innovation

    A survey published today suggested that technical debt is starting to take a heavier toll as IT environments continue to become more complex to manage.

    The survey of 400 IT leaders at organizations with 1,500 employees was conducted by Foundry, the market research arm of International Data Group (IDG) on behalf of Insight Enterprises, a provider of IT services. The survey found that 86% of respondents reported their organization was impacted by technical debt over the past 12 months, with the top areas affected being the ability to innovate (43%), meet service level agreements (41%) and avoid downtime (37%).

    Technical debt is created when organizations cut corners and leave known bugs in the race to meet application delivery deadlines. Application code is often not as thoroughly tested as it should be. In some cases, it turns out that what was intended to be a minimum viable product doesn’t scale all that well. Quick fixes needed to improve performance are also frequently undocumented. Inefficient code also winds up consuming more IT infrastructure than required, which adversely impacts everything from cloud costs to the amount of carbon generated.

    Juan Orlandini, chief architect for the Cloud + Data Center Transformation (CDCT) division of Insight Enterprises, said every organization struggles with technical debt; it will never be eliminated, but it does need to be contained, he added.

    The challenge is instead of trying to keep the proverbial IT lights on during the COVID-19 era, IT teams are now being asked to innovate to advance digital business transformation initiatives, said Orlandini. A full 87% of survey respondents cited modernizing critical applications as a key success driver.

    As a result, many organizations are embracing platform engineering to bring more structure to their DevOps processes, he noted. The challenge, however, is striking a balance between a more centralized approach to DevOps and maintaining the ability of developers to innovate, said Orlandini.

    The issue, of course, is that in addition to massive technical debt, the latest generation of applications are more distributed than ever. The survey found 91% of respondents now rely on multiple public cloud providers for different workloads, with 54% of data residing on a public cloud. However, the survey also found on-premises IT environments are still relevant, with 20% planning to repatriate select public cloud workloads to an on-premises model over the next 12 months.

    Nearly three-quarters (72%) of respondents also noted data volumes are growing faster than their ability to manage them, with 64% ranking implementation of a data governance program to improve data management as their top data-related objective this year. Just over a third (35%) of the data estate is now, on average, driven by edge workloads, with 29% of respondents reporting that at least 50% of data volumes now reside on the edge. Nearly two-thirds (64%) expected that to increase in the next 12 months.

    A total of 85% of respondents also indicated their organization is using artificial intelligence (AI) to some degree to drive business insights and/or efficiencies, although only 36% reported having optimized their use of AI and machine learning (ML) across the enterprise.

    Finally, cybersecurity also remains problematic, with 51% reporting they were impacted by a cybersecurity breach over the past 12 months. Just 20% resolved their issue in one day, while 31% needed less than a week. Nearly half (49%) required one week or more to recover.

    It’s clear that IT isn’t becoming any easier to manage. IT teams need to find ways to build and deploy new applications while reducing technical debt so it doesn’t strangle future innovation.

  • Fiberplane Adds Wasm Plug-in Framework for DevOps Notebook

    Fiberplane Adds Wasm Plug-in Framework for DevOps Notebook

    Fiberplane today announced it is extending the reach of a real-time collaboration notebook designed for DevOps teams by making available tools for building plug-ins based on the WebAssembly (Wasm) framework.

    Micha Hernandez van Leuffen, Fiberplane CEO, said these plug-ins, dubbed providers, will make it much simpler for anyone to connect the Fiberplane notebook to other DevOps tools and platforms.

    The Fiberplane notebook uses the same operational transformation algorithm used in Google Docs to enable teams to easily collaborate around a document or spreadsheet. The core platform itself is built in Rust and WebAssembly. That approach enables a DevOps team to, for example, write and run PromQL queries and display Prometheus charts alongside other data presented via an integrated graph. Wasm makes it possible to run those providers both in the browser and on a backend platform.

    Fiberplane also announced it is open sourcing its Provider Development Kit (PDK), written in Rust, to enable organizations or third-party developers to create additional plug-ins. A Fiberplane Daemon then executes the plug-ins. The overall goal is to provide an open format based on Wasm for consuming DevOps data, noted Hernandez van Leuffen.

    The full open source Fiberplane WebAssembly-based Plugin System includes a Fp-bindgen to provide the bindings generator for building plug-ins, the Provider Development Kit (PDK), a toolchain for building plug-ins, a set of pre-configured plug-ins for Prometheus, ElasticSearch, Sentry, Grafana Loki, Cloudwatch and a generic HTTP provider, the Fiberplane command line interface and the Fiberplane Daemon.

    Fiberplane is essentially taking the concept of notebooks used for collaboration by data science teams and applying it to DevOps workflows. The goal is to improve DevOps teams’ productivity by reducing the amount of time it takes to sort through multiple types and classes of DevOps data to resolve an issue.

    As IT environments become more distributed in the age of the cloud and microservices, troubleshooting issues now invariably spans the responsibilities of multiple members of an IT team. Fiberplane, in effect, makes it possible to spin up a virtual war room that enables the members of an IT organization to collaborate until the issue of the moment is resolved.

    The speed at which any IT issue is resolved has become a crucial metric. Given the complexity of IT environments, it’s inevitable that incidents will arise. Ideally, IT teams would discover those issues before they disrupt the business. However, in reality, the metrics organizations use to evaluate the effectiveness of a DevOps team are often how quickly IT issues are resolved once they are discovered. The longer it takes for a distributed DevOps team to marshal its resources, the more likely it becomes that team will be perceived as being inefficient—regardless of what level of application availability is actually achieved.

    Most DevOps teams have, of course, implemented a wide range of incident management best practices that create a level of muscle memory for responding to a wide range of issues. The trouble is there will always be unforeseen issues that arise. DevOps teams, as a result, need to find ways to quickly focus on an unpredictable issue that they didn’t anticipate.

  • More Java Apps Are Migrating to the Cloud

    More Java Apps Are Migrating to the Cloud

    A survey of 879 enterprise developers and architects from Vaadin, a provider of framework for building Java applications, found that, as part of modernization efforts, the pace at which Java applications are moving to the cloud is now accelerating.

    The survey found more than one-third (36%) of Java applications are already deployed in the public cloud. More than half of respondents (56%) are also already deploying some of their Java applications into Kubernetes or serverless environments. Nearly two-thirds (63%) said they planned to move more Java applications to the cloud over the next 24 months, the survey also found.

    Kim Weins, vice president of product and marketing at Vaadin, said the survey makes it clear that enterprise IT organizations are still highly committed to Java. Still, there is a clear shift underway in terms of where those applications are being deployed. More than a third of respondents (35%) said they have Java applications deployed on Amazon Web Services (AWS), while 22% have deployed them on the Microsoft Azure Cloud. Another 11% are running them on the Google cloud platform.

    This shift, however, will take time. Almost half (47%) of Java applications still need modernization. As a result, 63% of respondents planned to increase their investments in modernizing existing Java applications.

    Maintainability is the top-ranked motivation for modernizing Java applications (32%), followed by security (20%) and ongoing maintenance costs (10%), the survey found.

    The top three challenges in developing Java applications are building an intuitive and simple user interface (81%), upgrading the tech stack (81%) and ensuring app security (78%).

    There is also a shift underway in terms of the frameworks used to build and modernize applications using a more cloud-native approach. A full 70% of respondents use Spring today, but 50% also noted they are planning to increase their use of Spring Boot. Other Java frameworks used include Vaadin Flow, Quarkus, Hilla and React. While derivatives of Spring are the dominant framework, it appeared more organizations are at least evaluating other options, noted Weins.

    Most organizations are also integrating Java applications with modern tools for logging (72%), observability (61%) and single sign-on (53%), the survey found.

    The shift to Java 17 is also well underway, with nearly three-quarters of respondents (73%) using or planning to use it over the next year. More than a quarter (26%) are already on Java 17 or a later release. Another 21% are currently upgrading, while 26% plan to update in the next 12 months.

    Overall, the survey found Java is being widely used for both internal (64%) and customer-facing (62%) applications. Java is most often used to build full-stack Java apps (70%) and backends (69%), the survey found

    Finally, the survey found more than a third of respondents (38%) expected that finding and retaining developers would be a significant challenge in 2023.

    There are, of course, no shortage of options when it comes to deploying Java applications. Most organizations will deploy Java applications everywhere from the network edge to the cloud. The one thing all these applications will have in common is they will be written in a venerable programming language that itself has been modernized.

  • Akamai Makes Case For Next Era of Cloud Computing

    Akamai Makes Case For Next Era of Cloud Computing

    Akamai Technologies today unveiled a cloud computing service that combines its ability to deploy applications at the edge with the cloud platform it gained via its acquisition of Linode.

    Shawn Michels, vice president of product management for compute and apps at Akamai, said Akamai Connected Cloud will provide the foundation for running a new generation of modern applications that require access to both core infrastructure resources in the cloud alongside highly distributed edge computing services.

    As part of the effort to deliver that combination of services, in the second quarter Akamai is adding three sites in the U.S. to the 11 it already provides. In addition, Akamai revealed it had identified 10 additional cloud sites and 50 distributed edge computing sites that it will add throughout the rest of this year.

    As a long-time provider of a content delivery network, Akamai manages a massive distributed computing environment that spans 4,100 locations across 135 countries. The acquisition of Linode added a set of cloud computing services that enable Akamai to offer the same set of services, including CDN services, as cloud service providers.

    Akamai is now signaling it will compete more aggressively by discounting the egress fees charged whenever data is moved off a cloud platform. One of the most expensive and unpredictable costs is the egress fees cloud service providers charge whenever data is moved off their platforms, noted Michels.

    Finally, Akamai also revealed it has achieved ISO, SOC2 and HIPAA standards compliance for its services.

    Akamai is making a case for an alternative approach to cloud computing that it said will be optimized for both existing monolithic applications running on virtual machines and cloud-native applications based on containers and serverless computing frameworks. A recent survey of 458 development professionals, managers and senior leaders conducted by Techstrong Research, a sister entity of devopsy.kinsta.cloud, found 43% of respondents are considering adding additional cloud service providers in the next 12 months. Nearly two-thirds said they are at least considering, evaluating or are ready to buy from a trusted alternative cloud vendor, with 20% reporting they have already contracted with one.

    It’s not clear whether IT organizations might actually migrate existing applications from one cloud service provider to another. At the very least, Akamai expects that as new applications are developed, the company will be able to gain a larger share of the overall market.

    There’s no doubt that a new era of cloud computing is dawning as organizations look to deploy distributed applications that process and analyze data closer to the point where it is created and consumed. These applications will then share the results of the data processed at the edge with, for example, centralized data lakes that make it possible to analyze data collected across a distributed computing environment.

    The one thing DevOps teams can count on is that as this next era of cloud computing evolves, the management of IT environments will become much more challenging for all concerned.

  • Report Affirms Continued AWS Cloud Dominance

    Report Affirms Continued AWS Cloud Dominance

    A report published this week by Wiz, a provider of a cloud security platform, found more than half of organizations (57%) are using multiple clouds, with 22% currently using three or more platforms.

    However, the report also noted that 72% of all workloads are running on the Amazon Web Services (AWS) cloud. Among organizations that have more than one cloud platform, Microsoft Azure (41%) is the most common secondary platform (41%), while Google Cloud Platform (GCP) is the most used tertiary platform among organizations employing two or more clouds (44%).

    The report also noted 9% of AWS customers use managed database servers, compared to 87% in GCP and 82% in Azure. However, over 91% of companies also have non-managed database servers running in a cloud. In total, only 6% of companies use managed database servers exclusively, compared to 90% using a mix of managed and non-managed database servers, the report finds.

    The most widely deployed databases are PostgreSQL, Redis and MySQL, with 90% of organizations running at least one instance of a PostgreSQL server.

    Scott Piper, principal cloud security researcher for Wiz, said the report makes it clear that despite gains by Microsoft and Google, AWS remains the most dominant cloud service provider. Even after a decade, rival cloud service providers have not been able to overcome the first-mover advantage that AWS continues to enjoy. In many cases, a second or third cloud is being employed only because a single development team preferred it or an IT team assumed responsibility for it when their company acquired another organization using it, noted Piper.

    However, while most organizations have multiple accounts per cloud service provider, the report also found that the bulk of the application workloads are managed via only a handful of accounts, he added. That suggests more organizations are subject to higher levels of disruption in the event of an outage than many of them may realize, said Piper.

    One of the reasons so many organizations have a narrow range of accounts, of course, is they simply don’t have enough personnel. In fact, a general skills shortage also tends to limit the number of cloud platforms organizations might otherwise employ.

    Multiple cloud platforms also tend to exacerbate cybersecurity challenges. With the introduction of each additional cloud service, the overall size of the attack surface that needs to be defended expands. The Wiz report found 47% of organizations have at least one database or storage bucket publicly exposed to the internet. It can take less than 13 hours for cybercriminals to discover and access an exposed bucket with a guessable name, noted Piper.

    More challenging still are the number of application programming interfaces (APIs) that need to be secured as cloud service providers continue to add new services, he added.

    Ideally, organizations should be adopting a framework to harden privileges, encryption, authentication and connectivity and improve hygiene, otherwise known as PEACH, said Piper.

    Regardless of the approach to cloud computing, it’s apparent there’s still a long way to go before organizations are ready to embrace hybrid cloud computing spanning multiple clouds.

  • Cisco Bets on OpenTelemetry to Advance Observability

    Cisco Bets on OpenTelemetry to Advance Observability

    Cisco today announced a technology preview of a Cisco Full-Stack Observability Platform based on instances of open source OpenTelemetry agent software being advanced by the Cloud Native Computing Foundation (CNCF) to collect metrics, event, logs and distributed traces. The Cisco Full-Stack Observability platform will be available in June 2023.

    The platform, announced at a Cisco Live EMEA event in Amsterdam, Netherlands, will combine the capabilities of multiple Cisco platforms and technologies into a single offering.

    At the same time, the company also announced the bidirectional integration between its existing Cisco AppDynamics application life cycle management (ALM) tool and the Cisco ThousandEyes network monitoring platform beginning in April.

    Finally, Cisco is making available a Business Risk Observability offering to provide business risk scoring. Business Risk Observability combines capabilities of its Kenna Risk Meter tool—gained when Cisco acquired Kenna Security in 2021—with the ability to monitor business transactions through Cisco AppDynamics to provide better visibility into application security. In addition, Cisco has integrated its Panoptica application programming interface (API) management security tool and the Talos threat intelligence platform within the Business Risk Observability Platform.

    Carlos Pereira, a Cisco fellow and chief architect for strategy, incubation and applications at Cisco, said Cisco is moving to narrow the historic divide between application development and cybersecurity teams to enable organizations to adopt DevSecOps best practices and make it simpler to prioritize the remediation of vulnerabilities that are likely to have the most impact on the business.

    Like most providers of observability platforms, Cisco is betting that more applications will be instrumented as OpenTelemetry software continues to mature. Cisco is now the single largest contributor to this project, noted Pereira.

    OpenTelemetry will also play a critical role in improving application security as more applications become instrumented, he noted. In fact, a recent Cisco AppDynamics survey found more than three-quarters of respondents (76%) believed that DevSecOps is essential for organizations to effectively protect against a multi-stage security attack. However, only 43% reported their organization had started implementing DevSecOps workflows.

    Observability, of course, has always been a core DevOps tenet, but achieving and maintaining it is challenging. Most DevOps teams today aspire to maintain some level of continuous monitoring. However, as it becomes easier and less costly to instrument applications, interest is rising in observability platforms that make it simple to investigate anomalies indicative of an issue that could disrupt an application environment. Most of those observability platforms are infusing those platforms with machine learning algorithms to surface those anomalies as part of an effort to augment the capabilities of a DevOps team.

    Regardless of the approach to observability, many organizations will soon be trying to determine whether to rely on existing monitoring tools that make it possible to track pre-defined metrics. In some cases, there may still be a need for that legacy approach to managing IT. Still, in other instances, it may be possible to rationalize some of those platforms in favor of a more advanced approach that relies on a more advanced approach to achieving observability.

  • 5 Technologies Powering Cloud Optimization

    5 Technologies Powering Cloud Optimization

    Cloud optimization is the process of improving the performance, cost-effectiveness, and reliability of cloud computing resources and services. It involves identifying and addressing inefficiencies in cloud architecture, application design and resource utilization, as well as implementing best practices for security, scalability and disaster recovery. 

    The goal of cloud optimization is to maximize the benefits of cloud computing while minimizing the risks and costs associated with it. It is a multi-disciplinary process that may involve several key elements, such as:

    • Capacity planning: Evaluating the current and future resource requirements of your cloud environment and ensuring that the right amount of resources are available to meet your needs.
    • Resource utilization: Monitoring and managing the utilization of cloud resources to ensure that they are used efficiently and effectively.
    • Cost optimization: Minimizing the cost of cloud resources and services by identifying and addressing areas of inefficiency and waste, such as over-provisioning or underutilized resources.
    • Performance optimization: Improving the performance of cloud applications and services by optimizing network bandwidth, storage performance and database performance.
    • Security optimization: Enhancing the security of cloud resources and data by implementing best practices for access control, encryption and threat mitigation.
    • Scalability optimization: Making sure that your cloud environment can scale up or down as needed to meet changing resource demands.
    • Disaster recovery: Establishing a disaster recovery plan to ensure that your cloud environment can quickly recover from failures or outages.

    Why is Cloud Optimization Important?

    Optimization is important for several reasons, including:

    • Cost savings: By optimizing the use of cloud resources, organizations can reduce their cloud computing costs and ensure that they are only paying for what they actually need.
    • Improved performance: By optimizing cloud applications and services, organizations can improve the performance and responsiveness of their systems, leading to a better user experience and increased productivity.
    • Increased reliability: Optimization helps organizations to improve the reliability and availability of their cloud environment, reducing the risk of downtime and ensuring that their systems are always available when they are needed.
    • Better security: By implementing best practices for security, organizations can better protect their cloud resources and data, reducing the risk of data breaches and other security incidents.
    • Scalability: Cloud optimization enables organizations to scale their environment up or down as needed, ensuring that they always have the resources they need to support their growing business.
    • Improved agility: Organizations can be more agile and responsive to changing business needs, enabling them to quickly and effectively respond to new opportunities and challenges.

    5 Technologies Powering Cloud Optimization

    Cloud Cost Management

    Cloud cost management is a critical component of optimization that helps organizations to monitor and manage their cloud spend. The goal is to ensure that organizations are only paying for the cloud resources they actually need and that they are using those resources efficiently.

    Cloud cost management solutions (such as Azure Cost Management or AWS Trusted Advisor) provide detailed cost reports, usage analytics and cost optimization recommendations to help organizations understand their cloud spend and identify areas of inefficiency. For example, these solutions can:

    • Monitor and report on cloud resource usage: By monitoring the usage of resources, cloud cost management solutions can provide detailed cost reports that show how much an organization is spending on each resource, such as compute instances, storage and network traffic.
    • Automate cost optimization: Many cloud cost management solutions can automate cost optimization tasks, such as turning off unused resources or right-sizing instances to reduce waste.
    • Provide cost analysis and forecasting: These solutions can provide detailed cost analysis and forecasting to help organizations understand the impact of changes to their cloud environment and plan for future spending.

    Autoscaling

    Autoscaling is a technology that enables organizations to automatically scale their cloud resources up or down as needed to meet changing demands. The goal of autoscaling is to ensure that organizations always have the right amount of resources to support their workloads while minimizing costs and ensuring that their systems are always available when they are needed.

    Autoscaling works by monitoring the performance and usage of cloud resources, such as compute instances, storage and network traffic, and automatically adjusting the size of those resources to meet changing demand. For example, autoscaling can:

    • Add or remove instances as needed: If demand for a resource increases, autoscaling can automatically add more instances to meet that demand. If demand decreases, autoscaling can automatically remove instances to reduce waste.
    • Optimize resource utilization: Autoscaling can optimize the utilization of cloud resources by right-sizing instances to meet demand, ensuring that resources are not over-provisioned or underutilized.
    • Improve system availability: By automatically adding or removing resources as needed, autoscaling can ensure that systems are always available and responsive, reducing the risk of downtime and improving the user experience.

    API Gateway

    An API gateway is a server that acts as an intermediary between an application and one or more microservices. The API gateway is responsible for request routing, composition and protocol translation, which enables microservices to communicate with each other securely and efficiently.

    An API gateway can help with cloud optimization in several ways:

    • Load balancing: The API gateway can distribute incoming API requests to multiple microservices, improving the overall performance and reliability of the system. It can also provide features such as automatic failover and load balancing, which helps to ensure that the system remains available and responsive even in the face of high traffic volumes or other performance challenges.
    • Resource optimization: By acting as a single entry point for API requests, the API gateway can help to reduce the overall resource usage of the system. For example, it can cache frequently used data and serve it directly to clients without having to go back to the microservices, reducing the load on the underlying system.
    • Monitoring and management: API gateways provide a centralized management interface for the microservices, making it easier to monitor and manage the system as a whole. This includes features such as logging, monitoring and alerting, which can help to identify and resolve performance issues quickly and effectively.

    GitOps Platforms

    GitOps is a paradigm that helps automate application deployment and infrastructure provisioning. It typically involves using Git, an open source version control system, as a single source of truth for declarative infrastructure and applications. 

    GitOps aims to improve the developer experience by letting teams use their familiar software development tools to manage application and infrastructure changes.

    With GitOps, cloud optimization can be achieved by:

    • Automating the deployment process: GitOps automates the deployment process, reducing the risk of human error and speeding up the deployment process. This helps to ensure that resources are deployed consistently and correctly, improving the reliability and performance of the environment.
    • Managing cloud infrastructure as code: With GitOps, cloud infrastructure can be defined and managed as code, making version control and collaborating on configurations easier. This helps to optimize the use of resources and improve the overall efficiency of the cloud environment.
    • Improving collaboration and communication: GitOps enables teams to collaborate and communicate more effectively, reducing the risk of conflicts and delays. With Git, changes can be easily tracked, discussed and approved, improving the speed and quality of deployments.
    • Enforcing governance and compliance: GitOps provides a centralized and auditable record of all changes to the environment, making it easier to enforce governance and compliance requirements. This helps to improve the security and reliability of the cloud environment, reducing the risk of breaches and other security incidents.

    APM

    Cloud application performance management (cloud APM) is the practice of monitoring, analyzing and optimizing the performance of cloud-based applications. The goal is to ensure that these applications are available, responsive and performing optimally to meet the needs of users.

    These solutions provide a range of tools and capabilities for monitoring and optimizing cloud-based applications, including:

    • Performance monitoring: Cloud APM solutions monitor application performance in real-time, providing visibility into performance metrics such as response time, resource utilization and error rates.
    • Root cause analysis: These solutions can help identify the root cause of performance issues by providing detailed performance data and tracing information.
    • Capacity planning: Cloud APM solutions can provide detailed performance data and analytics to help organizations plan and optimize their application deployments.
    • Performance optimization: These solutions can provide recommendations for performance optimization, such as right-sizing cloud resources, reducing resource utilization and improving application design.
    • Continuous performance monitoring: These solutions can continuously monitor application performance, providing real-time visibility and alerting to help organizations quickly identify and resolve performance issues.

    Conclusion

    In conclusion, cloud optimization is critical for organizations looking to maximize the value and minimize the costs of their cloud deployments. By using technologies such as cloud cost management, autoscaling, API gateways, GitOps platforms and APM, organizations can improve availability, performance and efficiency while reducing costs and ensuring that they are always prepared to meet changing business needs. 

    These technologies provide the tools and capabilities necessary to monitor, analyze and optimize cloud-based applications, helping organizations to ensure that their deployments are always delivering the best possible value. By embracing optimization, organizations can stay ahead of the curve and ensure that their cloud deployments are always aligned with their business goals and objectives.

  • New Relic Bolsters Observability Platform

    New Relic Bolsters Observability Platform

    New Relic has updated its observability platform to include the ability to better detect and track errors in addition to monitoring vulnerabilities.

    At the same time, an instance of the New Relic observability platform that runs natively on the Microsoft Azure cloud platform is now also generally available.

    Manav Khurana, general manager for observability product and chief growth office for New Relic, said the alliance will enable Microsoft Azure customers to consume New Relic as part of their existing Microsoft Azure services contract.

    New Relic already provides an errors inbox to track issues, but is now adding a tool to track the impact an error might have by correlating data across traces and logs. The company has also integrated its platform with Slack to make it simpler for IT teams to generate alerts when vulnerabilities are introduced into codebases and manage errors more collaboratively.

    Similarly, New Relic is also looking to foster greater collaboration between software engineering and cybersecurity teams. A New Relic Vulnerability Management tool with no additional configuration required captures security signals generated via the company’s Telemetry Data Platform in a way that can be analyzed using an interactive application security testing (IAST) tool that New Relic gained with its acquisition of K2 Cyber Security. Additional IAST capabilities available in preview include the ability to leverage a patented deterministic technique to identify and provide automated vulnerability validation that highlights a proof-of-exploit.

    The overall goal is to provide more visibility and context for organizations that are implementing best DevSecOps practices, said Khurana.

    It’s still relatively early days as far as the integration of observability platforms into DevOps workflows is concerned. A recent survey conducted by New Relic found most organizations don’t expect to have robust observability practices in place by 2025. While most organizations have tools to monitor predefined metrics today, there is a significant gap between observability platforms that enable IT teams to determine the root cause of an IT issue and monitoring platforms that generate an alert whenever a threshold is exceeded.

    In fact, many organizations have too many monitoring tools that often surface conflicting or redundant alerts, noted Khurana.

    One way or another, more codebases are being instrumented. As that process continues to evolve, the agents embedded in that code make it simpler to collect the logs and traces needed to advance observability. The challenge, as always, is that it takes time for the number of fully instrumented applications to exceed the number of legacy applications that are either partially instrumented or not instrumented at all.

    As IT environments become more complex, the need for observability is becoming much more pressing at a time when most IT teams are more short-handed than ever, noted Khurana.

    Regardless of approach, there’s no doubt that observability, with patience, will impact the management of IT for the better.

  • Microsoft Outage Outrage: Was it BGP or DNS?

    Microsoft Outage Outrage: Was it BGP or DNS?

    Welcome to The Long View—where we peruse the news of the week and strip it to the essentials. Let’s work out what really matters.

    This week: All of Microsoft’s cloud services go down, everywhere except China. Redmond’s IaaS, PaaS and SaaS—including GitHub—were dead for several hours, and are still running unreliably—despite Microsoft saying it’s fixed the problem. (more…)