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You have set up a DevOps practice. Now, with the hard work done, you can sit back, relax, and witness the collaboration between your Dev and Ops teams as they deliver better quality software faster. The emerging concepts of working with DevOpsmetrics and DevOps KPIs have really come a long way. Dynatrace news.
DORA ( DevOps Research and Assessment ) metrics, developed by the DORA team have become a standard for measuring the efficiency and effectiveness of DevOps implementations. As organizations start to adopt DevOps practices to accelerate software delivery, tracking performance and reliability becomes critical.
DevOps and security teams managing today’s multicloud architectures and cloud-native applications are facing an avalanche of data. Find and prevent application performance risks A major challenge for DevOps and security teams is responding to outages or poor application performance fast enough to maintain normal service.
As organizations accelerate innovation to keep pace with digital transformation, DevOps observability is becoming a critical key to success for DevOps and DevSecOps teams. According to recent Dynatrace research , organizations expect to make software updates 58% more frequently in the coming year.
With the world’s increased reliance on digital services and the organizational pressure on IT teams to innovate faster, the need for DevOps monitoring tools has grown exponentially. In fact, the Dynatrace 2023 CIO Report found that 78% of respondents deploy software updates every 12 hours or less. What is DevOps monitoring?
Staying ahead of customer needs requires speed and agility from all phases of the software development life cycle (SDLC). DevOps automation can help to drive reliability across the SDLC and accelerate time-to-market for software applications and new releases. What is DevOps automation?
As more organizations embrace DevOps and CI/CD pipelines, GitHub-hosted runners and GitHub Actions have emerged as powerful tools for automating workflows. Everyone involved in the software delivery lifecycle can work together more effectively with a single source of truth and a shared understanding of pipeline performance and health.
Just as organizations have increasingly shifted from on-premises environments to those in the cloud, development and operations teams now work together in a DevOps framework rather than in silos. But as digital transformation persists, new inefficiencies are emerging and changing the future of DevOps.
As a result, IT operations, DevOps , and SRE teams are all looking for greater observability into these increasingly diverse and complex computing environments. In IT and cloud computing, observability is the ability to measure a system’s current state based on the data it generates, such as logs, metrics, and traces.
DevOps and platform engineering are essential disciplines that provide immense value in the realm of cloud-native technology and software delivery. Observability of applications and infrastructure serves as a critical foundation for DevOps and platform engineering, offering a comprehensive view into system performance and behavior.
But with many organizations relying on traditional, manual processes to ensure service reliability and code quality, software delivery speed suffers. As a result, organizations are investing in DevOps automation to meet the need for faster, more reliable innovation. Automation is a crucial aspect of achieving DevOps excellence.
By implementing service-level objectives, teams can avoid collecting and checking a huge amount of metrics for each service. When organizations implement SLOs, they can improve software development processes and application performance. SLOs improve software quality. SLOs promote automation. SLOs minimize downtime.
DevOps and ITOps teams rely on incident management metrics such as mean time to repair (MTTR). These metrics help to keep a network system up and running?, Other such metrics include uptime, downtime, number of incidents, time between incidents, and time to respond to and resolve an issue. So, what is MTTR?
When it comes to site reliability engineering (SRE) initiatives adopting DevOps practices, developers and operations teams frequently find themselves at odds with one another. Too many SLOs create complexity for DevOps. SLOs are a great way to define what software should do. Dynatrace news.
That’s especially true of the DevOps teams who must drive digital-fueled sustainable growth. All of these factors challenge DevOps maturity. Data scale and silos present challenges to DevOps maturity DevOps teams often run into problems trying to drive better data-driven decisions with observability and security data.
DevOps and site reliability engineering (SRE) teams aim to deliver software faster and with higher quality. We refer to this culture and practice as observability-driven DevOps and SRE automation. The role of observability within DevOps. The results of observability-driven DevOps speak for themselves.
With the most important components becoming release candidates , Dynatrace now supports the full OpenTelemetry specification on all runtimes and automatically adds intelligence to metrics at enterprise scale. So these metrics are immensely valuable to SRE and DevOps teams. Kudos and thanks to all fellow contributors.??.
Today, every organization is a software company, driven by demands for better, more connected digital experiences. To keep up, we’ve seen growing interest in DevOps and continuous delivery , as organizations aim to deliver new digital services and experiences faster. What is DevOps? DevOps is what we aspire to.
Today, the demand for software is higher than ever. Introduction. Lines of code govern almost everything we do in our day-to-day activities. The way we buy, the way we sell, even the way we communicate. In 2019, according to Evans Data Corporation, there were 23.9 million developers worldwide.
This leads to frustrating bottlenecks for developers attempting to build and deliver software. A central element of platform engineering teams is a robust Internal Developer Platform (IDP), which encompasses a set of tools, services, and infrastructure that enables developers to build, test, and deploy software applications.
Organizations can now accelerate innovation and reduce the risk of failed software releases by incorporating on-demand synthetic monitoring as a metrics provider for automatic, continuous release-validation processes. The ability to scale testing as part of the software development lifecycle (SDLC) has proven difficult.
In the world of DevOps and SRE, DevOps automation answers the undeniable need for efficiency and scalability. Though the industry champions observability as a vital component, it’s become clear that teams need more than data on dashboards to overcome persistent DevOps challenges.
As the new standard of monitoring, observability enables I&O, DevOps, and SRE teams alike to gain critical insights into the performance of today’s complex cloud-native environments. The architects and developers who create the software must design it to be observed. Observability defined.
One of the primary drivers behind digital transformation initiatives is the desire to streamline application development and delivery to bring higher quality, more secure software to market faster. Dynatrace enables software intelligence as code.
Why organizations are turning to software development to deliver business value. Digital immunity has emerged as a strategic priority for organizations striving to create secure software development that delivers business value. Software development success no longer means just meeting project deadlines.
Now, Dynatrace has the ability to turn numerical values from logs into metrics, which unlocks AI-powered answers, context, and automation for your apps and infrastructure, at scale. Whatever your use case, when log data reflects changes in your infrastructure or business metrics, you need to extract the metrics and monitor them.
Artisan Crafted Images In the Netflix full cycle DevOps culture the team responsible for building a service is also responsible for deploying, testing, infrastructure, and operation of that service. We now have the software and instance configuration as code. This means changes can be tracked and reviewed like any other code change.
This lets you build your SLOs around the indicators that matter to you and your customers—critical metrics related to availability, failure rates, request response times, or select logs and business events. Depending on the environment, the different information types provide indicators that reveal potential problems for your customers.
To remain competitive in today’s fast-paced market, organizations must not only ensure that their digital infrastructure is functioning optimally but also that software deployments and updates are delivered rapidly and consistently. They help foster confidence and consistency throughout the entire software development lifecycle (SDLC).
2020 cemented the reality that modern software development practices require rapid, scalable delivery in response to unpredictable conditions. Microservices are flexible, lightweight, modular software services of limited scope that fit together with other services to deliver full applications. Dynatrace news. Limited observability.
2020 cemented the reality that modern software development practices require rapid, scalable delivery in response to unpredictable conditions. Microservices are flexible, lightweight, modular software services of limited scope that fit together with other services to deliver full applications. Dynatrace news. Limited observability.
This is the question that drives many of us who work along the software-product lifecycle. Answering this question requires careful management of release risk and analysis of lots of data related to each release version of your software. Services and metrics that show version information will be added.
OpenTelemetry (also referred to as OTel) is an open-source observability framework made up of a collection of tools, APIs, and SDKs, that enables IT teams to instrument, generate, collect, and export telemetry data for analysis and understand software performance and behavior. Logs, metrics, and traces make up the bulk of all telemetry data.
In part one of this series , I talked through the common pain points software delivery teams face as they’re asked to support cloud adoption and modernization initiatives. Keptn eliminates the need for organizations to custom code scripts that tie together different DevOps tools of choice for delivery and operational automation.
Many software delivery teams share the same pain points as they’re asked to support cloud adoption and modernization initiatives. Automatically collect and evaluate business, service, and architectural indicator metrics to promote or roll back deployments. Key ingredients required to deliver better software faster.
A full-stack observability solution uses telemetry data such as logs, metrics, and traces to give IT teams insight into application, infrastructure, and UX performance. DevOps teams can also benefit from full-stack observability. With improved diagnostic and analytic capabilities, DevOps teams can spend less time troubleshooting.
Platform engineering is a practice that outlines how development teams build internal platforms to create self-service capabilities for software engineering teams. The result is a cloud-native approach to software delivery. DevOps and the platform engineer role In the world of DevOps, the role of platform engineers is relatively new.
According to leading analyst firm Gartner, “80% of software engineering organizations will establish platform teams as internal providers of reusable services, components, and tools for application delivery…” by 2026. Open source logs and metrics take precedence in the monitoring process. Platform engineering is on the rise.
The growing popularity of open source software presents new risks associated with vulnerable libraries. In response, organizations have adopted additional security tools, such as software composition analysis, that scan code libraries for vulnerabilities. What is software composition analysis?
As organizations look to expand DevOps maturity, improve operational efficiency, and increase developer velocity, they are embracing platform engineering as a key driver. The pair showed how to track factors including developer velocity, platform adoption, DevOps research and assessment metrics, security, and operational costs.
At Dynatrace’s 2020 Perform Conference, we shared approaches for how our customers are using Dynatrace to help them “ Release Better Software Faster ”. Environment interfaces include queries for topology, metrics, problems, and user sessions to name a few. Dynatrace news. The Dynatrace event API call is a single web request.
The Dynatrace Software Intelligence Hub helps enterprises easily apply AI to all technologies and data sources and unlock automation at scale. Just like the Dynatrace Platform, the Software Intelligence Hub is built with automation at its core. It requires a simple and automated approach to provide value at scale.
Problem remediation is too time-consuming According to the DevOps Automation Pulse Survey 2023 , on average, a software engineer takes nine hours to remediate a problem within a production application. With that, Software engineers, SREs, and DevOps can define a broad automation and remediation mapping.
For more information on how a data lakehouse powered by software intelligence can help your organization quell cloud complexity, create operational efficiencies, and deliver better business insights, view the resources below. For example, development teams can use automation to increase efficiency in the software development lifecycle.
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