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We’re excited to share that Dynatrace has been recognized in the DevOps: Observability category of InfoWorlds 2024 Technology of the Year awards! The post Dynatrace wins InfoWorlds 2024 Technology of the Year Award for DevOps: Observability appeared first on Dynatrace news. Register now !
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.
This is a mouthful of buzzwords” is how I started my recent presentations at the Online Kubernetes Meetup as well as the DevOps Fusion 2020 Online Conference when explaining the three big challenges we are trying to solve with Keptn – our CNCF Open Source project: Automate build validation through SLI/SLO-based Quality Gates. Dynatrace news.
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. They need automated DevOps practices.
As organizations accelerate innovation to keep pace with digital transformation, DevOps observability is becoming a critical key to success for DevOps and DevSecOps teams. DevOps and DevSecOps practices help organizations release software faster and more frequently, paving the way for digital transformation.
What should they do first to set your organization on the path to DevOps automation? By the time your SRE sets up these DevOps automation best practices, you have had to push unreliable releases into production. Most importantly, the right modern observability platform is key to a successful DevOps and SRE implementation.
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?
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.
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.
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. But according to the 2023 DevOps Automation Pulse , only 56% of end-to-end DevOps processes are automated.
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. Selenium.
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.
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.
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?
Their technology provides expert-level recommendations for SQL statements, vector search queries, indices, and database schemas, along with automated remediation actions. With Metis, were making database troubleshooting as seamless as any other part of the DevOps workflow.
To keep up, we’ve seen growing interest in DevOps and continuous delivery , as organizations aim to deliver new digital services and experiences faster. However, it isn’t as simple as just implementing a DevOps toolset, analyzing DevOps metrics, or investing in DevOps monitoring capabilities. What is DevOps?
DevOps metrics and digital experience data are critical to this. Breaking down the silos between IT and operations to form a DevOps team, and then extending this to other departments to achieve BizDevOps, has been central to reaching this goal. Dynatrace news. Every journey matters, and we have to deliver on every single transaction.”.
In response to the scale and complexity of modern cloud-native technology, organizations are increasingly reliant on automation to properly manage their infrastructure and workflows. DevOps automation eliminates extraneous manual processes, enabling DevOps teams to develop, test, deliver, deploy, and execute other key processes at scale.
As enterprises embrace more distributed, multicloud and applications-led environments, DevOps teams face growing operational, technological, and regulatory complexity, along with rising cyberthreats and increasingly demanding stakeholders. How do you make this happen?
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.
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.
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. With many pipelines to maintain, DevOps teams need automated orchestration. Dynatrace news.
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.
In May 2022, the Tech Transforms podcast explored the cybersecurity threat landscape, observability, DevOps, and remote work through our conversations with the following top influencers in government technology: Richard Ford – Chief Technology Officer at Praetorian. Dynatrace news. Observability Explained with Mike Maciag.
So how do development and operations (DevOps) teams and site reliability engineers (SREs) distinguish among good, great, and suboptimal SLOs? The state of service-level objectives While SLOs play a critical role in helping DevOps and SRE teams align technical objectives with business goals, they’re not always easy to define.
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 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.
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).
” [1] As modern enterprises adopt cloud technologies over time, they often end up with a heterogeneous mix of fragmented security products managed by siloed teams, resulting in complexity, a broadened attack surface, and a plethora of unanswered security questions. Security teams can use it for threat detection and governance.
We’re proud to announce that Ally Financial has presented Dynatrace with its Ally Technology Velocity with Quality award. This is the second time Ally Financial has presented its Ally Technology Partner Awards. The post Dynatrace proud to receive the Ally Technology Velocity with Quality award appeared first on Dynatrace news.
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.
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. Kelsey Hightower and Andreas Grabner discuss the future of cloud-native technologies appeared first on Dynatrace blog.
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.
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. For example, for companies with over 1,000 DevOps engineers, the potential savings are between $3.4
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.
In today's rapidly evolving technological landscape, the integration of Artificial Intelligence (AI) and Machine Learning (ML) with IT operations has become a game-changer. AIOps (Artificial Intelligence for IT Operations) is a cutting-edge solution that combines AI, ML, and automation to enhance DevOps practices and streamline IT operations.
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?
Horizons of creativity are now open to define new approaches for the implementation and understanding of DevOps methods and technologies. Moreover, organizations and IT teams expect an investment boost in methods, architecture, and tools.
Cloud-native technology has been changing the way payment services are architected. In 2020, I presented a series with insights from real implementations adopting open-source and cloud-native technology to modernize payment services. The major omission in this series was to avoid discussing any aspect of cloud-native observability.
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.
The research, which surveyed 1,300 CIOs and technology leaders from large organizations worldwide, highlights the pressing need for a mature AI, analytics, and automation strategy to overcome the challenges posed by modern cloud environments.
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.
Technology that helps teams securely regain control of complex, dynamic, ever-expanding cloud environments can be game-changing. But managing and securing these environments can be downright impossible without technology to identify and alert users to issues. DevOps and DevSecOps orchestration. Dynatrace news.
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