devopsy.kinsta.cloud

Category: Features

  • Harness Brings Generative AI Capabilities to DevOps Workflows

    Harness Brings Generative AI Capabilities to DevOps Workflows

    Harness today added a raft of generative artificial intelligence (AI) capabilities to its continuous integration/continuous delivery (CI/CD) platform as part of a larger effort to reduce the level of manual toil that today conspires to create DevOps bottlenecks.

    The added generative AI capabilities include an AI Development Assistant (AIDA), which analyzes log files and correlates error messages with known issues. It also includes the ability to use natural language to define policies for governing cloud assets and costs and an ability to automatically identify security vulnerabilities and generate code fixes.

    Other generative AI capabilities that will be added to AIDA over the next three to six months include automated code reviews along with tools for creating pipelines and launching chaos engineering experiments.

    Harness CEO Jyoti Bansal said these are the first of a series of generative AI capabilities that will be applied across the entire software development life cycle (SDLC) using large language models (LLMs) that the company has trained using publicly available sources. AIDA, at its core, provides a tool for creating custom prompts for launching queries against LLMs and a vector database that Harness has incorporated into its platform.

    That approach means no customer data was used to create the model and none of the data used will find its way into a generative AI platform that is available to anyone, said Bansal. As a result, organizations don’t need to be concerned they light run afoul of licensing issues because proprietary code was inadvertently included in an LLM, he added.

    Most of the existing generative AI capabilities that have been brought to market thus far are designed primarily to improve developer productivity, noted Bansal. Harness is now bringing the benefit of generative AI to DevOps teams that today rely on too many manual processes to manage the automations they build on behalf of application development teams, he added.

    Harness is making AIDA available at no extra charge at a time when many DevOps teams will soon be evaluating the AI capabilities provided to them. Most DevOps teams are not going to want to manage workflows without being able to rely on AI to reduce toil and eliminate bottlenecks. Overall, Harness is forecasting generative AI will drive a 30% to 50% increase in DevOps productivity. In addition, Harness is forecasting there will be a 50% to 75% reduction in the time spent remediating vulnerabilities.

    Bansal said that as that process occurs, Harness is betting more organizations will move to replace legacy CI/CD platform with more modern alternatives.

    Previously, Harness has invested in machine learning algorithms to automate a range of DevOps tasks. Generative AI, in combination with machine learning, will transform DevOps workflows in ways that will ultimately improve both the rate at which applications can be built and their overall quality.

    It’s not clear whether organizations might be willing to replace CI/CD platforms that they have been customizing for decades, but at the very least, that option is now more widely considered than ever.

  • Quali Adds Governance and Cloud Cost Control Tools to Automation Platform

    Quali Adds Governance and Cloud Cost Control Tools to Automation Platform

    Quali today revealed it added governance and cloud cost management tools to its Torque platform for automating IT infrastructure management.

    David Williams, senior vice president for market strategy at Quali, said the added governance tools will make it possible to enforce security, compliance and consumption policies as IT environments are launched using the automation blueprints that Torque enables IT teams to create.

    At the same time, IT teams can now also define consumption policies based on cloud runtime or regions employed within a cloud computing environment. In addition to taking advantage of dashboards to visualize consumption of cloud resources, IT teams can also use Torque to identify cloud waste including detached, inactive and overprovisioned instances. They can pause, right-size or tear down environments to reduce costs and eliminate the possibility of a billing surprise at the end of the month, noted Williams.

    Torque also enables IT teams to detect drift and then update live cloud environments to remediate any that fall out of scope, he added.

    Quali has been making a case for an environment-as-a-service approach to managing IT. That approach is based on a set of triggers for controlling infrastructure via a software-as-a-service (SaaS) platform that can be invoked either via an application programming interface (API) or a graphical user interface (GUI).

    In addition to providing a set of infrastructure provisioning guardrails that prevent mistakes from being made, Torque makes it possible to automatically deploy complete application environments on top of infrastructure provisioned as code using blueprints rather than relying on low-level Terraform scripts. The goal is to increase developer productivity by enabling IT teams to create self-service portals that developers can use to spin up environments.

    That approach is becoming more appealing as many organizations begin to adopt platform engineering as a method to centralize the management of DevOps workflows, noted Williams. In fact, as part of that effort, many organizations are starting to unify the management of cloud and on-premises IT environments, he added.

    While many developers routinely provision IT infrastructure using tools such as Terraform, many of them lack the cybersecurity expertise required to ensure cloud computing environments are configured properly. Developers also tend not to remember to de-provision cloud resources when no longer needed; over time, those factors contribute to unnecessarily increased cloud costs.

    Ultimately, the goal is to find ways to centrally manage IT environments to reduce costs and improve cybersecurity without inhibiting the pace at which developers are building innovative applications, said Williams.

    At the same time, as application environments become more complex, it is becoming even more challenging to provision and manage IT environments at a time when many organizations are reluctant to hire additional IT staff, he noted.

    One way or another, IT environments will become more automated. The issue is determining how best to organize the IT teams managing those environments as tasks that once required a lot of manual effort are increasingly automated.

  • Leaders in Resilience See ROI From Observability

    Leaders in Resilience See ROI From Observability

    Observability is maturing throughout the software industry. Observability is often defined as merging metrics, logs and traces to get a fuller picture of an application’s state. This can help pinpoint disruptions or security incidents and offer a clearer path to remediation. Observability is touted to advance the application monitoring practices of yesteryear, but are investments paying off?

    According to recent findings, many organizations are using observability tools and seeing a positive outcome. A full 73% of organizations reported using observability tools for over a year. And impressively, 86% of observability leaders said the ROI on their observability tools has exceeded their expectations. The practice appears to be paying dividends for organizations that have gone “all-in” with mature observability processes.

    The State of Observability 2023 report released by Splunk demonstrated how observability leaders are reaping a positive return from observability tools. According to the report, observability is helping to meet performance expectations, avoid downtime and enhance resilience in general. However, not all organizations are on the observability maturity bandwagon. Below, we’ll examine some of the key trends from the report and consider the benefits of refining your observability efforts.

    Now that observability is more commonplace, dedicated roles are emerging to support these initiatives. In fact, 87% of respondents now employ specialists who work exclusively on observability projects. Site reliability engineers likely make up a portion of these experts, as observability data can be used to advance efforts around meeting service-level objectives (SLOs).

    But although observability might be more common than a few years ago, not every observability practice is mature or standardized. Just 40% have a formal approach to resilience that has been institutionalized organization-wide. Because of this, only 43% are confident in their team’s ability to meet its application reliability and performance objectives. It should be noted that this number increases significantly for those with more mature observability adoption, which we’ll expand on below.

    Furthermore, not all applications are cloud-native. Organizations reported operating and maintaining, on average, 165 internally developed business applications, half of which are hosted in the public cloud and half of which are on-premises. Due to the persistence of legacy modalities, observability tools must continue to support a hybrid architecture if they are to be comprehensive and useful.

    And although we’ve previously covered how many organizations are drowning in a sea of observability data, observability leaders now say their ROI on observability tools far exceeded their expectations. Perhaps this indicates that, with more open standards, analysis centralization and fewer false positives, teams are finding ways to avoid observabiliy tooling sprawl.

    Lastly, the report unveiled desires to loop AI and ML into the observability pipeline. In fact, 66% of observability teams already use AI/ML, while 26% are in the process of deploying the technology. And 91% said AIOps is an important enabler of their observability goals. Certainly, AI is becoming a pervasive instrument to accelerate many areas, including observability.

    Benefits of Observability

    An impressive 64% reported that their investment into observability has exceeded their expectations. So, what are some of the top benefits of observability? Well, the report found the topmost benefits to be areas like decreasing problem detection and resolution times, identifying “true positive” incidents, and enhancing application security.

    Observability is being deployed as a tool to evolve traditional security efforts, as it uncovers a deeper understanding of application behaviors. This can help security teams correlate errors to specific diagnoses and spot potential threats in a quick manner. As such, 59% said observability helps them uncover security issues thanks to the intelligence capabilities of observability solutions. And 55% say they can uncover more security vulnerabilities thanks to the visibility afforded by observability.

    Observability can also be used to improve visibility into hybrid architectures. A full 86% said it’s important to have flexible observability solutions that cover hybrid architectures, though half identify this as an area for improvement. Although we like to think that cloud-native development is the status quo, many enterprises still oversee a mixture of on-premises, private cloud and multi-cloud environments. A unified, agnostic observability layer is thus essential to peek into all these disparate environments to grapple with disparate data outputs.

    The Leaders of the Observability Pack Win

    Service interruptions can have negative consequences for organizations, including lower customer satisfaction, loss of revenue and loss of customers. In fact, 76% of respondents reported downtime can cost up to $500,000 per hour.

    Thankfully, observability has emerged to help improve overall resilience and avoid these negative repercussions. But, to truly reap the benefits, you must have a mature practice in place. As defined by the report, “observability leaders” have a more formal approach to resilience and have standardized this across their organization. And 89% of those leaders are completely confident in their ability to meet their application availability and performance requirements. The catch-22 with observability is that you must invest more energy into formalization and knowing when the effort is worthwhile is a moving target.

    A solid observability practice is supported by standardized metrics, logs and traces across the organization. Furthermore, to make observability behave correctly, you will need flexible tooling that can leverage data from multiple sources, such as the network, infrastructure, servers and databases.

    The State of Observability 2023 report surveyed 1,750 observability practitioners from around the globe, making it the most extensive study on observability to date. For more insights, you can pick up a copy of the report behind an email gate here.

  • Five Great DevOps Job Opportunities

    Five Great DevOps Job Opportunities

    DevOps.com is now providing a weekly DevOps jobs report through which opportunities for DevOps professionals will be highlighted to better serve our audience.

    Our goal in these challenging economic times is to make it easier for DevOps professionals to advance their careers.

    Of course, the pool of available DevOps talent is still relatively constrained, so when one DevOps professional takes on a new role it tends to create an opportunity for others.

    The five job postings shared this week are selected based on the company looking to hire, the vertical industry segment and, naturally, the pay scale being offered.

    We’re also committed to providing additional insights into the state of the DevOps job market. In the meantime, for your consideration:

    Indeed.com

    SAP
    San Francisco, California
    DevOps Engineer
    $141,378 to $162,000

    LinkedIn

    Colgate-Palmolive
    Piscataway, New Jersey
    DevOps Lead
    $112,000 to $164,800

    CareerBuilder.com

    Northrup Grumman
    Dulles, Virginia
    Principal DevOps Engineer
    $104,600 to $157,000

    SimplyHired

    Crate & Barrel
    Northbrook, Illinois
    DevOps Engineer
    $99,100 to $125,000

    Dice.com

    Tata Elxsi Ltd.
    Philadelphia, Pennsylvania
    DevOps Engineer
    $80,000 to $100,000

  • Pulumi Embeds Terraform Conversion Tool in Platform

    Pulumi Embeds Terraform Conversion Tool in Platform

    At its virtual PulumiUP event, Pulumi this week announced it embedded an ability to convert instances of Terraform into its infrastructure-as-code (IaC) platform via a simple command line interface (CLI) command. In addition, Pulumi added a Review Stacks capability that automatically creates a dedicated cloud environment to review code every time a pull request is opened.

    Pulumi is also making available a beta release of Pulumi Azure Native Provider 2.0, which decreases the size of the software development kit (SDK) by 60%. This is part of an effort to improve deployment times and reduce resource consumption by, for example, removing support for deprecated application programming interfaces (APIs).

    Finally, Pulumi has added support for property names and values to Resource Search for Pulumi Cloud, a search and analytics tool for cloud computing environments. DevOps teams can now additionally search for instances of, for example, versions of databases or specific availability zone as a result.

    Aaron Kao, vice president of marketing for Pulumi, said previously the company made available a separate tool for converting snippets of Terraform code. For the first time, Pulumi is also making available a converter plugin in the Pulumi engine which allows conversion tools from other IaC tools to be used.

    Review Stacks, meanwhile, makes it simpler for DevOps teams to pick up an unfamiliar codebase, make changes to both application and infrastructure code and share a live environment to review that code.

    Pulumi has been making a case for an alternative to Terraform that centralizes the management and provisioning of infrastructure using a set of embedded guardrails. One of the major issues enterprise IT organizations are encountering these days is the number of misconfigurations created when developers use tools like Terraform to provision infrastructure on their own. Those misconfigurations often lead to, for example, ports being left open and cybercriminals exfiltrating data.

    That approach is gaining traction among enterprise customers that are looking to centralize the management of DevOps processes, said Kao.

    In the wake of a series of high-profile breaches, more organizations are now reviewing the security of their software supply chains, including how infrastructure is provisioned. Many of those organizations will need to revisit those processes as pending legislation that requires more stringent requirements for building software eventually become law, noted Kao.

    At the same time, many organizations are also looking to improve the productivity of DevOps teams during an economic downturn that limits the number of full-time employees they might be able to hire. The pace at which software is being developed has not slowed, so there is a greater urgency to do more with less.

    It’s not clear how quickly organizations are centralizing the management of DevOps workflows, but with the rise of platform engineering, there is clearly more interest in defining consistent backend processes that multiple DevOps teams are currently managing individually. The challenge is finding a way to achieve that goal without impeding the pace of innovation enabled by embracing DevOps in the first place.

  • 92% of Devs Use AI, Survey Says ¦ Intel One Mono Font

    92% of Devs Use AI, Survey Says ¦ Intel One Mono Font

    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: GitHub touts unbelievable AI stats, and Intel’s beautiful open source typeface. (more…)

  • How Open Source Can Enhance Developer Experience

    How Open Source Can Enhance Developer Experience

    Developer experience (DX) is becoming more and more of a competitive advantage among developer-facing tools and platforms. A great developer experience that’s easy to follow and implement can truly help a software tool stand out from the crowd.

    Simultaneously, open source software is all the rage. In fact, a recent StackOverflow survey found open source software (OSS) to be, by far, the most revered and proven technology trend.

    With that in mind, what are the synergies between developer experience and open source? And how can building in an open source format aid the developer experience for your public-facing toolsets and internal development platforms?

    I recently met with Adam Frank, SVP of product and marketing at Armory, to explore the state of developer experience and open source adoption. According to Frank, open source can bring numerous DX benefits. Below, we’ll explore these areas and consider why organizations might benefit from adopting more open source within their developer-facing initiatives.

    The State of Developer Experience and Open Source

    So, what is the state of developer experience, and why is it important now? Well, DX is continually leveraged to help improve agility and competitiveness in the market. In addition to granting differentiation, DX also enables more flexibility, helping users switch from one tool to another if necessary.

    “Developer experience is at the forefront right now because technology and change are moving faster than ever before,” said Frank. “Companies need to focus on DX as a competitive advantage to survive and thrive.” At the same time, open source can help organizations move quickly and iterate more efficiently.

    Yet, historically, open source has not been associated with fantastic DX. Most of us have at least one horror story of an open source project simply going belly-up without warning. It’s common for an OSS tool to lack comprehensive documentationor suffer from a lack of funding for ongoing maintenance, zero customer support and deprecated modules. Some tools that developers directly download and contribute to may not possess a quality DX emphasis, says Frank.

    However, the status quo for OSS has undoubtedly evolved over the years, he adds. Nowadays, there are more established groups, like Linux Foundation’s Cloud Native Computing Foundation (CNCF), with specific Technical Oversight Committees (TOCs) to oversee individual projects. The maturity of OSS ownership now ensures core projects stay relevant and receive continual support—not to mention ongoing developer experience enhancements.

    On the other side, OSS is often absorbed by a platform team to enable their internal developers to move faster or ship more code, says Frank. From this perspective, open source communities give platform engineering the opportunity to contribute back to the project, helping them solve deeper-level problems that are more specific to their environments.

    How Open Source Can Enhance Developer Experience

    Not all IT leaders are sold on the idea of building in a transparent, open source model. Yet, this enhanced transparency can bring dividends in the long run, especially where developer experience is considered. Frank shared some of the benefits of adopting open source.

    Receiving Feedback From The Community

    “As a product manager, you want as much feedback from your users as you can gather,” said Frank. Receiving user feedback is a great way to fix DX issues, and OSS gives you that on a larger scale. By adopting open source, you benefit from collecting insights from your customer base and the developer community at large. This can translate into a broader range of use cases, which can significantly improve projects and overall experience.

    Increasing Ecosystem Transparency

    Building in a more transparent and open fashion so that everyone has the ability to submit pull requests can also help you work together with potential partners. This makes it easier to develop third-party integrations that ensure the broader ecosystem can work together. By decreasing the barrier to entry through OSS, you provide others with the ability to solve more problems around developer experience.

    Streamlining the Developer Toolchain

    “Developers want to innovate; they want to solve problems,” said Frank. Open source can also help expose inefficiencies in the developer toolchain and, notably, many open source CI/CD tools are often leveraged to automate deployment and increase efficiency. The end result is that developers can focus on innovating their own competitive advantage. “Making the deployment aspect of the developer lifecycle really seamless can significantly improve their experience,” he said. Therefore, any tools or extensions around CI/CD are an excellent area to consider open-sourcing.

    Increasing Flexibility

    Another benefit of the open source model is that you have far more flexibility than off-the-shelf proprietary software. As a customer, you don’t have to wait to submit enhancement requests. With OSS, you can fork a project or quickly collaborate with the maintainers. This equates to making fixes far quicker and providing the ability to customize developer experiences to the tasks at hand.

    Best Practices to Ensure Open Source Improves DX

    Open source provides many key benefits that can enhance software development and delivery. But, this should be taken with a grain of salt, as best practices still must be followed to ensure open source enhances, not hinders, developer experience.

    For example, Frank mentions that simplicity should be a guiding light. “Have simplicity for the user experience design in the forefront of everything you’re building and thinking about,” said Frank. Adopting simplicity should help ensure developer-facing materials are structured well and documented in an easy-to-comprehend manner.

    On that note, open source projects will require standards around areas like good documentation and well-written APIs that abide by contracts, said Frank. Anything less will hinder developers and confuse them with disparate data formats. On that note, he has witnessed OpenTelemetry emerge as a common way to unify data that systems produce with standard formatting, which increases the observability of these environments.

    Lastly, it’s critical to hire talent with experience in open source. Bringing in folks that have knowledge of how OSS communities operate will make onboarding easier and encourage safer open source security practices as well.

    What the Future of DX and OSS Holds

    Open source appears to aid developer experience in many ways, from driving more innovation, opening software up to feedback and developing a closer-nit developer community. But what does the future of developer experience and open source look like?

    According to Frank, we will likely see increased data standardization that makes it easy to work with various projects and data formats. OpenTelemetry, for example, makes aggregating logging easier. We’ve also seen standardization around OpenAPI Specification for describing web APIs. Another example is FinOps Foundation’s FOCUS specification to unify cost analysis.

    Open source tends to leverage open source. And as the industry continues to coalesce around open standards, we’ll likely see more robust, compatible layers of abstraction emerge throughout the market, Frank predicts.

  • BMC Adds Generative AI Capabilities to Helix Management Platform

    BMC Adds Generative AI Capabilities to Helix Management Platform

    BMC today revealed it is embedding generative artificial intelligence (AI) capabilities across its BMC Helix service and operations management platforms.

    BMC CTO Ram Chakravarti said the company is incorporating the open source GPT-J large language models (LLMS) to build generative AI models. Those models are optimized for specific domains using data collected by BMC and imported from other data sources, like the Jira project management software from Atlassian. That persistent layer of storage is designed to aggregate multiple types of data within what amounts to a Helix data lake.

    The generative AI capabilities added to BMC’s portfolio include natural language summaries of issues and events captured by BMC Helix Operations Management, along with an ability to create a historical analysis of a user’s specific environment to identify recurring issues more easily.

    BMC Service Management, meanwhile, can now correlate incidents and provide resolution summaries that can be stored. It’s also now possible to run clustering analysis on chat archives to find new or improved utterances that help virtual agents answer queries better and execute workflows.

    BMC initially opted to build its own LLMs because general-purpose LLMs—such as the one created by OpenAI—are subject to “hallucinations.” Hallucinations are created when incorrect data is included in a model. BMC is training its LLMs on a narrow range of trusted data to ensure the recommendations and subsequent automations it creates are valid.

    Over time, BMC will add additional LLMs; the company hasn’t yet decided if there are use cases where it makes sense to rely on an existing general-purpose LLM to add additional capabilities, noted Chakravarti.

    Organizations can also opt to use a containerized version of the BMC LLM if they prefer, but BMC will encourage most organizations to invoke generative AI via its Helix SaaS platform, he added.

    BMC Helix is an IT services management (ITSM) platform that integrates with a range of DevOps platforms. Helix is part of a larger existing BMC Connected Digital Ops initiative that seeks to unify ServiceOps and DevOps with AIOps, DataOps and AutonomousOps. Generative AI will automate a range of tasks from within Helix that can then be extended to DevOps platforms such as Jenkins.

    It’s still early days as far as applying generative AI to processes, so organizations should focus on use cases where it will add some immediate value, said Chakravarti. Once they develop a level of trust in the automation created and executed, they can then pragmatically expand the number of generative AI use cases where they make sense, he added.

    One way or another, generative AI is going to be applied to the management of IT. Many routine tasks that conspire to limit the productivity of IT teams today will be eliminated, but there will always be a need for a human to remain in the loop to ensure the right outcomes are achieved. However, it will also soon become possible for existing teams to manage IT at levels of scale that were previously unattainable.

    Image source: Photo_Credite_Indira-Tjokorda via Unsplash

  • HashiCorp Releases Slew of Updates to Improve DevSecOps

    HashiCorp Releases Slew of Updates to Improve DevSecOps

    At a HashiDays event this week, HashiCorp launched updates to its Terraform implementation and a software-as-a-service offering, dubbed HCP Vault Secrets, that promise to simplify infrastructure security and ensure that secrets are not leaked.

    In addition, HashiCorp has added a self-hosted edition of its remote access security tool, Boundary, that can now also record SSH sessions. The company is also announcing general availability of Vault Secrets Operator, which provides a high level of abstraction for managing secrets in a Kubernetes environment and which synchronizes with the secrets management interfaces defined by the Kubernetes Technical Oversight Committee.

    Finally, HashiCorp is making available in beta a 1.16 update to the Consul service mesh for containers and virtual machines that adds a Sameness Groups capability to improve the resiliency of microservices by redirecting requests to an identical service. HashiCorp has also added a transparent proxy mode to enable failover between services along with a permissive mutual TLS (mTLS) that enables a service to be configured to accept both mTLS traffic from mesh-enabled services and non-Consul mTLS traffic from external downstream applications.

    Chris Van Wesep, senior director of product marketing for HashiCorp, said Version 1.5 of HashiCorp Terraform adds config-driven import workflow and check blocks capabilities that make it possible to declaratively use code to add existing resources into a Terraform state. Previously, the only way to update a Terraform state was to use an import command that could only be applied to one resource at a time. Terraform 1.5 also adds automatic code-generation capabilities for imported resources.

    In addition, version 1.5 of Terraform also includes a tool to validate that provisioned infrastructure is behaving as intended. That latter capability makes it possible to reduce the number of misconfigurations created by developers that might one day be exploited by cybercriminals to breach an IT environment.

    HCP Vault Secrets, meanwhile, provides a beta release of a SaaS edition of the existing Vault offering specifically designed to enable organizations to better manage application secrets that might inadvertently be exposed to cybercriminals in a production environment, said Van Wesep.

    HashiCorp is moving toward providing a portfolio of tools that enable DevOps teams to securely provision and manage hybrid cloud computing environments using a common workflow, he noted. A Forrester Consulting survey found nearly three-quarters (73%) of respondents are reporting this strategy is helping them reach their business goals, with another 19% adding they expected this strategy to help them achieve their business goals in the next year.

    It’s not clear whether organizations are fully embracing multi-cloud computing, but each additional cloud added to an enterprise IT environment increases the total cost of IT. The only way to mitigate those costs is to define a set of best practices for building and deploying applications that can be applied to any cloud computing environment.

    Unfortunately, many organizations will discover that, as they attempt to define those best practices, they have inadvertently become dependent on a set of proprietary application programming interfaces (APIs) that thwart those efforts.

  • Grafana Labs Slashes Time to Create Observability Dashboards

    Grafana Labs Slashes Time to Create Observability Dashboards

    At its GrafanaCON 2023 event today, Grafana Labs updated its core platform for visualizing data which makes it simpler to set up dashboards in minutes. The updates are part of a celebration of the 10th anniversary of a tool that is now widely used by DevOps teams.

    Ryan McKinley, a distinguished engineer for Grafana Labs, said Grafana 10 should help make DevOps more accessible to a wider range of practitioners with limited experience working with observability tools. The latest release also makes it simpler to share knowledge with external stakeholders via public dashboards, he added.

    In addition, Grafana 10 adds expanded role-based access control (RBAC) capabilities and streamlined implementation of the secure access markup language (SAML) to ensure authentication.

    Grafana Cloud has also been updated to provide a secure way to connect to data residing in an on-premises IT environment or in a cloud with the observability platform the company provides via a software-as-a-service (SaaS) platform.

    Finally, Grafana Labs is also making the engine it created to visualize data more accessible to third-party developers that are embedding visualizations based on Grafana within their applications, noted McKinley.

    Grafana Labs

    There are now more than 150 plugins for various data sources that have been made available to more than 20 million users of the Grafana visualization framework. Not all those users are working in DevOps environments, but Grafana is widely used to enable observability across increasingly complex IT environments. The Grafana Cloud seeks to capitalize on that popularity by adding a service that uses an instance of open source Grafana Mimir software to store data collected in a format originally defined for the open source Prometheus monitoring tool.

    It’s still early days as far as adoption of observability is concerned, but it’s apparent that as application environments become more complex, the plethora of monitoring tools that DevOps teams rely on will need to be streamlined. Observability platforms promise to unify logs, metrics and traces to simplify launching queries to identify the root cause of an issue.

    The rate at which DevOps teams will embrace observability will naturally vary, but the biggest obstacle might not be the platforms themselves. Instead, the issue is understanding what queries can help DevOps teams better understand the root cause of an IT issue before there is a major disruption. In the long term, it’s expected that machine learning algorithms will leverage the data collected by observability platforms to automatically identify issues that might lead to a disruption long before it actually occurs.

    Of course, the result of any query that gets launched needs to be visualized in a way that is easily understood. Grafana Labs is now making a case for a more integrated approach that, at its core, employs its visualization tools to make it simpler to discern what’s occurring in IT environments. After all, no matter how talented any DevOps team may be, it’s still not possible to manage what was never seen in the first place.