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DevOps and security teams managing today’s multicloud architectures and cloud-native applications are facing an avalanche of data. Indeed, around 85% of technology leaders believe their problems are compounded by the number of tools, platforms, dashboards, and applications they rely on to manage multicloud environments.
Takeaways from this article on DevOps practices: DevOps practices bring developers and operations teams together and enable more agile IT. Still, while DevOps practices enable developer agility and speed as well as better code quality, they can also introduce complexity and data silos. Dynatrace news.
As organizations accelerate innovation to keep pace with digital transformation, DevOps observability is becoming a critical key to success for DevOps and DevSecOps teams. This drive for speed has a cost: 22% of leaders admit they’re under so much pressure to innovate faster that they must sacrifice code quality.
DevOps seeks to accomplish smooth and efficient software creation, delivery, monitoring, and improvement by prioritizing agility and adaptability over rigid, stage-by-stage development. What is DevOps? As DevOps pioneer Patrick Debois first described it in 2009, DevOps is not a specific technology, but a tactical approach.
But to be scalable, they also need low-code/no-code solutions that don’t require a lot of spin-up or engineering expertise. According to recent Dynatrace data, 59% of CIOs say the increasing complexity of their technology stack could soon overload their teams without a more automated approach to IT operations and automated workflows.
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? DevOps automation is a set of tools and technologies that perform routine, repeatable tasks that engineers would otherwise do manually.
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. But when and how does DevOps monitoring fit into the process? And how do DevOps monitoring tools help teams achieve DevOps efficiency?
As cloud-native, distributed architectures proliferate, the need for DevOpstechnologies 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? Atlassian Jira.
As 2023 shifts into the rearview mirror, technology and business leaders are preparing their organizations for the upcoming year. And industry watchers have begun to make their technology predictions for 2024. Data indicates these technology trends have taken hold. Technology prediction No. Technology prediction No.
The events of 2020 accelerated the trend of organizations shifting to cloud-native technologies in response to the dramatic increase in demand for online services. 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?
You have set up a DevOps practice. As we look at today’s applications, microservices, and DevOps teams, we see leaders are tasked with supporting complex distributed applications using new technologies spread across systems in multiple locations. DevOps metrics to help you meet your DevOps goals.
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.
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.
Many organizations realize their DevOps tools and practices do not sufficiently account for security. This is known as “security as code” — the constant implementation of systematic and widely communicated security practices throughout the entire software development life cycle. The security challenges of DevOps.
DevOps and platform engineering are essential disciplines that provide immense value in the realm of cloud-native technology and software delivery. Rather, they must be bolstered by additional technological investments to ensure reliability, security, and efficiency. However, these practices cannot stand alone.
That’s especially true of the DevOps teams who must drive digital-fueled sustainable growth. All of these factors challenge DevOps maturity. Teams need a technology boost to deal with managing cloud-native data volumes, such as using a data lakehouse for centralizing, managing, and analyzing data. What is DevOps maturity?
When it comes to site reliability engineering (SRE) initiatives adopting DevOps practices, developers and operations teams frequently find themselves at odds with one another. Developers want to write high-quality code and deploy it quickly. Too many SLOs create complexity for DevOps. Limits of scripting for DevOps and SRE.
Many organizations that have integrated their software development and operations into DevOps practices struggle with efficiency because they’re juggling disparate DevOps tools, or their tools aren’t meeting their needs. The status quo of the DevOps toolchain. Buchanan urges teams to consider where time is spent.
The DevOps approach to developing software aims to speed applications into production by releasing small builds frequently as code evolves. As part of the continuous cycle of progressive delivery, DevOps teams are also adopting shift-left and shift-right principles to ensure software quality in these dynamic environments.
More technology, more complexity The benefits of cloud-native architecture for IT systems come with the complexity of maintaining real-time visibility into security compliance and risk posture. Runtime Security integrates seamlessly with static code analyzers, container scanners, and application security testing tools.
DevOps and site reliability engineering (SRE) teams aim to deliver software faster and with higher quality. What these steps have in common is that monitoring tools are not in sync with new changes in code or topology and this observability data is often siloed within different tools and teams. The role of observability within DevOps.
The DevOps approach to developing software aims to speed applications into production by releasing small builds frequently as code evolves. As part of the continuous cycle of progressive delivery, DevOps teams are also adopting shift-left and shift-right principles to ensure software quality in these dynamic environments.
The IT world is rife with jargon — and “as code” is no exception. “As code” means simplifying complex and time-consuming tasks by automating some, or all, of their processes. Today, the composable nature of code enables skilled IT teams to create and customize automated solutions capable of improving efficiency.
AWS is on a journey to revolutionize DevOps using the latest technologies. We are starting to treat DevOps, and the toolchains around it, as a data science problem – And when we think of it this way, code, logs, and application metrics are all data that we can optimize with machine learning (ML).
These are two values he shares with DevOps activist Andreas Grabner, who sat down with Hightower at Dynatrace Perform 2022 to talk about taming Kubernetes and the future of cloud-native technologies. Infrastructure as code vs infrastructure as data. Not everyone knows how to write code,” he says. “As
Infrastructure as code is a way to automate infrastructure provisioning and management. In this blog, I explore how Dynatrace has made cloud automation attainable—and repeatable—at scale by embracing the principles of infrastructure as code. Infrastructure-as-code. But how does it work in practice? Cloud Automation use cases.
Recently, Dynatrace added OpenTelemetry support to its PurePath 4 technology, which is its fourth and latest generation of automatic and intelligent distributed tracing. Configuring monitoring and observability is no stranger to that paradigm and it was also highlighted in the latest State of DevOps 2020 report.
In this blog post, we describe how we improved the methodology, which technologies we leveraged, and how this has improved service deployment and consistency. We now have the software and instance configuration as code. This means changes can be tracked and reviewed like any other code change.
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. Gartner characterizes observability as the evolution of traditional monitoring capabilities in response to the demands of cloud-native technologies.
We’re currently in a technological era where we have a large variety of computing endpoints at our disposal like containers, Platform as a Service (PaaS), serverless, virtual machines, APIs, etc. And, applying the “Everything as Code” principles can greatly help achieve that. Benefits of Everything as Code.
GPT (generative pre-trained transformer) technology and the LLM-based AI systems that drive it have huge implications and potential advantages for many tasks, from improving customer service to increasing employee productivity. It highlights the potential of GPT technology to drive “information democracy” even further.
As organizations grapple with mounting cloud complexity, IT teams know they must identify and respond to evolving issues across the entire technology stack—from mainframes to multicloud environments. Endpoints include on-premises servers, Kubernetes infrastructure, cloud-hosted infrastructure and services, and open-source technologies.
DevSecOps is a cross-team collaboration framework that integrates security into DevOps processes from the start rather than waiting to address security in a separate silo. How is it different from DevOps, and what’s next for the relationship between development, security, and operations within enterprises? What is DevSecOps?
In fact, according to the recent Dynatrace survey , “The state of AI 2024,” the majority of technology leaders (83%) say AI has become mandatory. Alongside the numerous benefits, these organizations need to manage the increased risks the technology brings. This means greater productivity for individual teams.
If cloud-native technologies and containers are on your radar, you’ve likely encountered Docker and Kubernetes and might be wondering how they relate to each other. In a nutshell, they are complementary and, in part, overlapping technologies to create, manage, and operate containers. Dynatrace news. But first, some background.
This complex web of interconnected technologies across a containerized environment introduces various challenges related to visibility, resource utilization, security, orchestration, and collaboration. Monitoring-as-code can also be configured in GitOps fashion. Ensure that you get the most out of your product.
Which technology trends are fueling business digital transformation? AI and DevOps, of course The C suite is also betting on certain technology trends to drive the next chapter of digital transformation: artificial intelligence and DevOps. DevOps can also reduce human error throughout the software deployment process.
.” As more organizations expand services via the cloud and demand for digital services increases, SRE practices are essential to meet up-time service level agreements, and to meet the continuous-integration/continuous-delivery (CI/CD) demands of DevOps and DevSecOps teams. SRE bridges the gap between Dev and Ops teams.
This year’s AI Breakthrough Awards attracted over 2,000 nominations from the best companies, technologies, products , and services in the field of AI / AIOps. Dynatrace automatically collects data not just from metrics, traces, and logs, but also user experience and code-level insights – all in context and mapped into a topology.
According to recent Dynatrace data, 59% of CIOs say the increasing complexity of their technology stack could soon overload their teams without a more automated approach to IT operations. See how Dynatrace Log Management and Analytics enables any analysis at any time with Grail technology. Learn more. What is IT automation? Learn more.
In an article published by The Register’s Tom Claburn, Dynatrace chief technology strategist Alois Reitbauer shares his insights on the transformative role Kubernetes played in initiating the cloud-native movement. He explains how this open source project has set the industry standard for container orchestration since its inception.
IDC predicted, by 2022, 90% of all applications will feature microservices architectures that improve the ability to design, debug, update, and use third-party code. Combined with Agile or DevOps approaches and methodologies, enterprises can accelerate their ability to deliver digital services. .” Hard on DevOps.
Open source code, for example, has generated new threat vectors for attackers to exploit. 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. However, these technologies can increase complexity.
Amazon Web Services (AWS) and other cloud platforms provide visibility into their own systems, but they leave a gap concerning other clouds, technologies, and on-prem resources. To address these issues, organizations that want to digitally transform are adopting cloud observability technology as a best practice. Learn more here.
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