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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?
Cloud-native environments bring speed and agility to software development and operations (DevOps) practices. So which is it: SRE vs DevOps, or SRE and DevOps? DevOps is focused on optimizing software development and delivery, and SRE is focused on operations processes. DevOps as a philosophy.
Organizations are increasingly adopting DevOps to stay competitive, innovate faster, and meet customer needs. By helping teams release new software more frequently, DevOps practices are an essential component of digital transformation. Thankfully, DevOps orchestration has evolved to address these problems.
As enterprises expand their software development practices and scale their DevOps pipelines, effective management of continuous integration (CI) and continuous deployment (CD) processes becomes increasingly important. GitHub, as one of the most widely used source control platforms, plays a central role in modern development workflows.
As cloud-native, distributed architectures proliferate, the need for DevOps technologies and DevOps platform engineers has increased as well. DevOps engineer tools can help ease the pressure as environment complexity grows. ” What does a DevOps platform engineer do? A DevOps platform engineer is a more recent term.
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.
As organizations mature on their digital transformation journey, they begin to realize that automation – specifically, DevOps automation – is critical for rapid software delivery and reliable applications. In turn, manual approaches to identifying code issues and troubleshooting are not scalable.
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.
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.
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.
Software industry IT leaders face constant pressure to deliver innovation faster to stay ahead of their competition. According to the latest Dynatrace research , which polled 150 IT leaders in software organizations, 81% of respondents say digital transformation has accelerated in the past 12 months.
These software platform solutions helps users easily manage their database operations without having to really understand any of the abstractions. This is a great choice for DevOps in particular because it allows for more developer agility, productivity, and also security. Outsourced Security and Administration.
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.
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.
With growing multicloud complexity and the need for organization-wide scalability, self-service and automation capabilities have become increasingly essential for developer productivity. The result is a cloud-native approach to software delivery. In response to this shift, platform engineering is growing in popularity.
In the dynamic realm of modern software development and operations, terms such as Platform Engineering, DevOps, and Site Reliability Engineering (SRE) are frequently used, sometimes interchangeably, often causing confusion among professionals entering or navigating these domains.
As recent events have demonstrated, major software outages are an ever-present threat in our increasingly digital world. From business operations to personal communication, the reliance on software and cloud infrastructure is only increasing. Software bugs Software bugs and bad code releases are common culprits behind tech outages.
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. The ability to effectively manage multi-cluster infrastructure is critical to consistent and scalable service delivery.
Many software delivery teams share the same pain points as they’re asked to support cloud adoption and modernization initiatives. Key ingredients required to deliver better software faster. Successful DevOps teams have figured out that “delivering more with less” requires careful management of release risks and automation to scale.
The DevOps playbook has proven its value for many organizations by improving software development agility, efficiency, and speed. These methods improve the software development lifecycle (SDLC), but what if infrastructure deployment and management could also benefit? GitOps improves speed and scalability. Dynatrace news.
As Porsche Informatik migrated from a monolithic environment to a containerized, hybrid-cloud landscape, OpenShift facilitated greater agility and scalability of their Kubernetes-orchestrated DevOps projects, boosting both the company’s ability to innovate and reduce time to market. Want to try it and see for yourself?
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).
When thousands of lives are at risk, software infrastructure can make the difference between life and death. That’s why traceability, scalability, and reliability are crucial aspects of a cloud strategy, and for this county, OpenShift and Dynatrace delivered on these needs.
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. Our goal is to make this process simple, scalable, and enjoyable.
Site reliability engineering (SRE) is the practice of applying software engineering principles to operations and infrastructure processes to help organizations create highly reliable and scalablesoftware systems. ” According to Google, “SRE is what you get when you treat operations as a software problem.”
To implement SLOs in your software delivery cycle and consistently add observability measures from the beginning, Dynatrace “configuration as code” (Monaco and Dynatrace Terraform) will soon support the new API. At the same time, dedicated configuration-as-code support in Monaco and Terraform will provide a scalable, automated solution.
Cloud-native applications now dominate IT as DevOps teams respond to growing demands to deliver functionality faster and more securely. As DevOps teams are pivoting to cloud-native technologies, IT environments have become increasingly complex. Cloud technologies enable teams to deploy and release software more frequently.
Just like shipping containers revolutionized the transportation industry, Docker containers disrupted software. The time and effort saved with testing and deployment are a game-changer for DevOps. This opens the door to auto-scalable applications, which effortlessly matches the demands of rapidly growing and varying user traffic.
Process Improvements (50%) The allocation for process improvements is devoted to automation and continuous improvement SREs help to ensure that systems are scalable, reliable, and efficient. SREs invest significant effort in enhancing software reliability, scalability, and dependability.
Site reliability engineering (SRE) is the practice of applying software engineering principles to operations and infrastructure processes to help organizations create highly reliable and scalablesoftware systems. ” According to Google, “SRE is what you get when you treat operations as a software problem.”
As modern agile software development relies heavily on automated CI/CD pipelines to swiftly build and deploy releases multiple times daily, these pipelines must be reliable and high-performing. Consequently, troubleshooting issues and ensuring seamless software deployment becomes increasingly tricky.
Dynatrace scored highest across 4 of 5 use cases, DevOps/AppDev, SRE/CloudOps, IT Operations, and Digital Experience Monitoring, and second highest in the Application Owner/Line of Business use case. We anticipated the industry’s move to dynamic multicloud environments and DevOps processes.
Software companies who have already been following and adopting DevOps and site reliability engineering (SRE) practices alongside their shared ancestry in agile concepts came out on top – especially if they adopted those practices across the whole organization and customer value stream.
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.
They can develop software applications rapidly and gain access to extensible cloud resources without having to sink costs into IT plumbing or managing this infrastructure themselves. Considering open source software (OSS) libraries now account for more than 70% of most applications’ code base, this threat is not going anywhere anytime soon.
For software engineering teams, this demand means not only delivering new features faster but ensuring quality, performance, and scalability too. This involves new software delivery models, adapting to complex software architectures, and embracing automation for analysis and testing.
This is both frustrating for companies that would prefer making ML an ordinary, fuss-free value-generating function like software engineering, as well as exciting for vendors who see the opportunity to create buzz around a new category of enterprise software. Can’t we just fold it into existing DevOps best practices?
As strained IT, development, and security teams head into 2022, the pressure to deliver better, more secure software faster has never been more consequential. A key arrow in the quiver for game-changers for developing and managing modern software is automatic, intelligent observability. DevOps and DevSecOps orchestration.
As a result, IT operations, DevOps , and SRE teams are all looking for greater observability into these increasingly diverse and complex computing environments. In these modern environments, every hardware, software, and cloud infrastructure component and every container, open-source tool, and microservice generates records of every activity.
Without the ability to see the logs that are relevant to your service, infrastructure, or cloud function—at exactly the right time and in exactly the right format—your cloud or DevOps engineers lose the ability to find the root causes of the issues they troubleshoot. In some deployment scenarios, you might skip CloudWatch altogether.
The end goal, of course, is to optimize the availability of organizations’ software. While I am excited that the people who create software are also responsible for it – in contrast to “throw over the wall” approaches – it poses consistency and compliance challenges in larger organizations. Note that the work doesn’t get reduced.
Instead, 95% of IT leaders in the retail sector say extending a DevSecOps culture to more teams and applications will be key to accelerating digital transformation and driving faster, more secure software delivery. Retail IT leaders must find ways to empower their teams to innovate faster without sacrificing software quality and security.
Event logging and software tracing help application developers and operations teams understand what’s happening throughout their application flow and system. In short, log management is how DevOps professionals and other concerned parties interact with and manage the entire log lifecycle.
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