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“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.
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.
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. 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.
At the time when I was building the most innovative observability company, security seemed too distant. I realized that our platforms unique ability to contextualize security events, metrics, logs, traces, and user behavior could revolutionize the security domain by converging observability and security.
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 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 fact, this is one of the major things that [hold] people back from really adopting DevOps principles.”
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?
To meet this demand, organizations are adopting DevOps practices , such as continuous integration and continuous delivery, and the related practice of continuous deployment, referred to collectively as CI/CD. Continuous delivery seeks to make releases regular and predictable events for DevOps staff, and seamless for end-users.
We’re excited to announce several log management innovations, including native support for Syslog messages, seamless integration with AWS Firehose, an agentless approach using Kubernetes Platform Monitoring solution with Fluent Bit, a new out-of-the-box ingest dashboard, and OpenPipeline ingest improvements.
With constraints on IT resources, downtime shifts staff away from innovation and other strategic work. Kailey Smith, application architect on the DevOps team for Minnesota IT Services (MNIT), discussed her experience with an outage that left her and her peers to play defense and fight fires. Dynatrace truly helps us do more with less.
When it comes to site reliability engineering (SRE) initiatives adopting DevOps practices, developers and operations teams frequently find themselves at odds with one another. The goal is to accelerate innovation by eliminating the need for custom automation scripts and point-to-point tool integrations. Dynatrace news.
We are pleased to announce Atlassian has selected Dynatrace as a launch partner for its Open DevOps initiative, which combines Atlassian products and best-in-class solutions from key partners to deliver full lifecycle value to customers. Visit the Atlassian Marketplace to explore the integrations today.
At the Dynatrace Innovate conference in Barcelona, Bernd Greifeneder, Dynatrace chief technology officer, discussed key examples of how the Dynatrace observability platform delivers value well beyond traditional monitoring. With Grail, for example, a DevOps team can pre-scan logs. The plattorm can pre-analyze and classify logs.
Today, speed and DevOps automation are critical to innovating faster, and platform engineering has emerged as an answer to some of the most significant challenges DevOps teams are facing. With higher demand for innovation, IT teams are working diligently to release high-quality software faster.
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 methodology—which brings development and ITOps teams together—also forwards digital transformation. And according to Statista , $2.4
Navigate digital infrastructure complexity In today’s rapidly evolving digital environment, organizations face increasing pressure from customers and competitors to deliver faster, more secure innovations. The effectiveness of this automation relies on the quality of the underlying data.
This improves the current project and paves the way for future innovation. The Dynatrace integration leverages native features and events that pass through the pipeline. Events serve as logic operators that can trigger or stop subsequent tasks within the pipeline. It also returns valuable time back to the SRE team.
NoOps, or “no operations,” emerged as a concept alongside DevOps and the push to automate the CI/CD pipelines as early as 2010. For most teams, evolving their DevOps practices has been challenging enough. The need for developers and innovation is now even greater. Thus, the concept of NoOps takes DevOps a step further.
Every year at our annual user conference, Dynatrace Perform , we recognize the most inspiring success stories from our most innovative, transformative customers and partners. DevOps: companies who shorten innovation cycles, automate their CI/CD pipelines , and improve code quality for production. These are individual awards.
While the benefits of AIOps are plentiful — including increased automation, improved event prioritization and incident response, and accelerated digital transformation — applying AIOps use cases to an organization’s real-world operations issues can be challenging. CloudOps includes processes such as incident management and event management.
Amplify PowerUP, our half-yearly global event to update our partner community, covered a lot of ground including key Partner Program announcements, Q2 earnings and partner contribution, market growth and momentum, Dynatrace platform capabilities, and the partner services offering the platform powers. DevOps and Cloud Ops Automation.
In this section, we explore how cloud observability tools differ from traditional monitoring: cloud-native observability platforms identify the root causes of anomalous events and provide automated incident response. Its approach to serverless computing has transformed DevOps. DevOps/DevSecOps with AWS. Learn more here.
They now use modern observability to monitor expanding cloud environments in order to operate more efficiently, innovate faster and more securely, and to deliver consistently better business results. Check out the guide from last year’s event. DevOps metrics and digital experience data are critical to this. Learn more.
For example, 73% of technology leaders are investing in AI to generate insight from observability, security, and business events data. DevOps teams , for example, can focus on driving innovation instead of grinding through manual jobs. This means greater productivity for individual teams.
Gartner defines AIOps as the combination of “big data and machine learning to automate IT operations processes, including event correlation, anomaly detection, and causality determination.” And how can it support your organization? What is AIOps? Two approaches to AIOps. What are the components of a modern AIOps solution?
In the past, monolith architectures could only be implemented with big bang deployments which result in a slow pace of innovation and significant downtime. Dynatrace provides built-in features, such as tagging, adding deployment events, and request tagging to mark and compare deployments for performance and feature parity.
Containers are the key technical enablers for tremendously accelerated deployment and innovation cycles. The time and effort saved with testing and deployment are a game-changer for DevOps. Event logs for ad-hoc analysis and auditing. But first, some background. Why containers? In production, containers are easy to replicate.
The Business Events capability enables business analysts to get the real-time insights and broad context they need to answer questions their business intelligence tools can’t. The post Data lakehouse innovations advance the three pillars of observability for more collaborative analytics appeared first on Dynatrace news.
AIOps combines big data and machine learning to automate key IT operations processes, including anomaly detection and identification, event correlation, and root-cause analysis. AIOps aims to provide actionable insight for IT teams that helps inform DevOps, CloudOps, SecOps, and other operational efforts. Aggregation.
A log is a detailed, timestamped record of an event generated by an operating system, computing environment, application, server, or network device. DevOps teams often use a log monitoring solution to ingest application, service, and system logs so they can detect issues at any phase of the software delivery life cycle (SDLC).
With the increasing adoption of agile software development, DevOps , progressive continuous delivery, and Site Reliability Engineering (SRE) practices, many companies are aiming to deliver better software faster and more safely while keeping up with customer demands. Following the evaluations, the results are logged in Dynatrace as events.
As businesses take steps to innovate faster, software development quality—and application security—have moved front and center. Indeed, according to one survey, DevOps practices have led to 60% of developers releasing code twice as quickly. With AIOps, algorithms observe events in context. Dynatrace news.
Autonomous Cloud Enablement (ACE) and Keptn – the Event-Driven Autonomous Cloud Control Plane – are helping our Dynatrace customers to automate their delivery and operations processes. Dynatrace news. There’s more from Christian and the rest of the Keptn and Autonomous Cloud community that we can all benefit from.
We are pleased to announce Atlassian has selected Dynatrace as a launch partner for its Open DevOps initiative, which combines Atlassian products and best-in-class solutions from key partners to deliver full lifecycle value to customers. Visit the Atlassian Marketplace to explore the integrations today.
Centralization of platform capabilities improves efficiency of managing complex, multi-cluster infrastructure environments According to research findings from the 2023 State of DevOps Report , “36% of organizations believe that their team would perform better if it was more centralized.”
Deploying and safeguarding software services has become increasingly complex despite numerous innovations, such as containers, Kubernetes, and platform engineering. Organizations strive to strike a delicate balance between cost, time to market, and innovation. Organizations must balance many factors to stay competitive.
The focus on bringing various organizational teams together—such as development, business, and security teams — makes sense as observability data, security data, and business event data coalesce in these cloud-native environments. Only 27% of those CIOs say their teams fully adhere to a DevOps culture.
Closing the loop (or not) : In the event of a successful solution, the platform informs the appropriate teams and closes the loop. It is also a key metric for organizations looking to improve their DevOps performance. Since this automation largely removes manual intervention, developers have greater bandwidth for innovation.
‘Composite’ AI, platform engineering, AI data analysis through custom apps This focus on data reliability and data quality also highlights the need for organizations to bring a “ composite AI ” approach to IT operations, security, and DevOps. Check back here throughout the event for the latest news, insights, and announcements.
Understanding the difference between observability and monitoring helps DevOps teams understand root causes and deliver better applications. This poses a dilemma for application teams responsible for innovation: How can they comply with ever-increasing security requirements while managing fast release cycles for hundreds of microservices?
.” 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.
As a result, IT operations, DevOps , and SRE teams are all looking for greater observability into these increasingly diverse and complex computing environments. An advanced observability solution can also be used to automate more processes, increasing efficiency and innovation among Ops and Apps teams. But what is observability?
But when these teams work in largely manual ways, they don’t have time for innovation and strategic projects that might deliver greater value. Predictive AI empowers site reliability engineers (SREs) and DevOps engineers to detect anomalies and irregular patterns in their systems long before they escalate into critical incidents.
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