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To get a better idea of OpenTelemetry trends in 2025 and how to get the most out of it in your observability strategy, some of our Dynatrace open-source engineers and advocates picked out the innovations they find most interesting. Second, it enables efficient and effective correlation and comparison of data between various sources.
This article is the second in a multi-part series sharing a breadth of Analytics Engineering work at Netflix, recently presented as part of our annual internal Analytics Engineering conference. Need to catch up? Check out Part 1.
AV1 is one of the most efficient codecs available today. The commitment to innovation and quality underscores our dedication to delivering an immersive and authentic viewing experience for all ourmembers. We enabled HDR10+ on Netflix using the AV1 video codec that was standardized by the Alliance for Open Media (AOM) in 2018.
This enables Dynatrace customers to achieve faster time-to-value and accelerate innovation. As a MISA member, we look forward to collaborating with Microsoft and other members to develop best practices, share insights, and drive innovation in cloud-native security. Click here to read our full press release.
Dynatrace partners are a cornerstone of our success, driving innovation and enabling customer growth. Were thrilled to announce the winners of this competition, who demonstrated exceptional innovation and creativity in their solutions.
At the time when I was building the most innovative observability company, security seemed too distant. In dynamic and distributed cloud environments, the process of identifying incidents and understanding the material impact is beyond human ability to manage efficiently. For example, user behavior helps identify attacks or fraud.
From developers leveraging platform engineering tools to optimize application performance, to Site Reliability Engineers (SREs) ensuring resilience, and executives gaining critical business insights, observability increases the velocity of innovation across every level of an organization.
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.
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. Further, automation has become a core strategy as organizations migrate to and operate in the cloud. What is a data lakehouse?
In the trending landscape of Machine Learning and AI, companies are tirelessly innovating to deliver cutting-edge solutions for their customers. However, amidst this rapid evolution, ensuring a robust data universe characterized by high quality and integrity is indispensable.
Such fragmented approaches fall short of giving teams the insights they need to run IT and site reliability engineering operations effectively. However, the drive to innovate faster and transition to cloud-native application architectures generates more than just complexity — it’s creating significant new risk.
This standardization enhances adoption within the personalization stack, simplifies the system, and improves understanding and debuggability for engineers. They must also provide enough information for partner engineers to identify the problem with the underlying service in cases of system-level issues.
At Dynatrace, we’ve been exploring the many ways of using GPTs to accelerate our innovation on behalf of our customers and the productivity of our teams. ChatGPT and generative AI: A new world of innovation Software development and delivery are key areas where GPT technology such as ChatGPT shows potential.
Our mission in Studio Engineering is to build a unified, global, and digital studio that powers the effective production of amazing content. In an effort to effectively and efficiently produce this content we are looking to improve and automate many areas of the production process. link] Why Does Studio Engineering Exist?
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.
Platform engineering is on the rise. 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. Automation, automation, automation.
Planned effort Site Reliability Engineering (SRE) effort and time allocation planning typically fall into two domains: Operations Management (50%) Operations Management includes on-call responsibilities, post-mortem assessments, addressing other interruptions, and buffer time. Streamlining the CI/CD process to ensure optimal efficiency.
I spoke with Martin Spier, PicPay’s VP of Engineering, about the challenges PicPay experienced and the Kubernetes platform engineering strategy his team adopted in response. Taking a strategic Kubernetes platform engineering approach Spier noted that keeping Kubernetes simple requires a strategic approach. Cost efficiency.
On Episode 52 of the Tech Transforms podcast, Dimitris Perdikou, head of engineering at the UK Home Office , Migration and Borders, joins Carolyn Ford and Mark Senell to discuss the innovative undertakings of one of the largest and most successful cloud platforms in the UK. Make sure to stay connected with our social media pages.
These benefits are then extended to the customers on our managed platform for them to drive more efficiency and better business outcomes. This consultative approach has led to better results and made the implementation of Dynatrace cost-efficient. Our journey with Dynatrace has been strategic from the beginning. Faster time to value.
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. And how do DevOps monitoring tools help teams achieve DevOps efficiency? Lost efficiency. What is DevOps monitoring?
What is site reliability engineering? Site reliability engineering (SRE) is the practice of applying software engineering principles to operations and infrastructure processes to help organizations create highly reliable and scalable software systems. Dynatrace news. SRE focuses on automation. SRE requires a cultural change.
Software should forward innovation and drive better business outcomes. Conversely, an open platform can promote interoperability and innovation. Legacy technologies involve dependencies, customization, and governance that hamper innovation and create inertia. Data supports this need for organizations to flex and modernize.
When it comes to platform engineering, not only does observability play a vital role in the success of organizations’ transformation journeys—it’s key to successful platform engineering initiatives. The various presenters in this session aligned platform engineering use cases with the software development lifecycle.
If a node is encountering performance-level issues, Davis [the Dynatrace AI engine] will pinpoint them,” Schirrmacher says. Ultimately, better infrastructure management enables organizations like Park ‘N Fly to innovate through software. IT automation speeds code development. You’re going to be able to resolve the issues.
This is done by extending our Davis AI engine with a new capability that considers domain and topology knowledge. This saves valuable time for engineers and architects for innovation.” The post Prevent potential problems quickly and efficiently with Davis exploratory analysis appeared first on Dynatrace news.
Site reliability engineering (SRE) continues to gain popularity as organizations embrace hybrid cloud strategies and IT automation at scale. By applying software engineering principles to operations and infrastructure practices, SRE enables organizations to streamline and automate IT processes. Dynatrace news.
Learning #1: To a large extent, development teams still rely heavily on Operations engineers. According to our survey, on average, four developers have one Operations engineer to support them. The size and complexity of today’s cloud environments will continue to expand with the speed and innovation required to remain competitive.
By Karen Casella, Director of Engineering, Access & Identity Management Have you ever experienced one of the following scenarios while looking for your next role? Most backend engineering teams follow a process very similar to what is shown below. If so, we invite you to begin the interview process.
When we launched the new Dynatrace experience, we introduced major updates to the platform, including Grail ™, our innovative data lakehouse unifying observability, security, and business data, and Dynatrace Query Language ( DQL ) for accessing and exploring unified data.
Site reliability engineering (SRE) is the practice of applying software engineering principles to operations and infrastructure processes to help organizations create highly reliable and scalable software systems. Dynatrace news. ” According to Google, “SRE is what you get when you treat operations as a software problem.”
Furthermore, it was difficult to transfer innovations from one model to another, given that most are independently trained despite using common data sources. Key insights from this shiftinclude: A Data-Centric Approach : Shifting focus from model-centric strategies, which heavily rely on feature engineering, to a data-centric one.
The Challenge of Title Launch Observability As engineers, were wired to track system metrics like error rates, latencies, and CPU utilizationbut what about metrics that matter to a titlessuccess? Stay tuned for a closer look at the innovation behind thescenes! The stakes are even higher when ensuring every title launches flawlessly.
Data Engineers of Netflix?—?Interview Interview with Pallavi Phadnis This post is part of our “ Data Engineers of Netflix ” series, where our very own data engineers talk about their journeys to Data Engineering @ Netflix. Pallavi Phadnis is a Senior Software Engineer at Netflix.
These criteria include operational excellence, security and data privacy, speed to market, and disruptive innovation. As a result, Ally is driving a new level of operational efficiency and saving millions in annual licensing costs. “We Dynatrace is especially proud to support innovators like Ally Financial.
While conventional video codecs remain prevalent, NN-based video encoding tools are flourishing and closing the performance gap in terms of compression efficiency. How do we apply neural networks at scale efficiently? In order to have a viable solution, we took several steps to improve efficiency.
More seamless handoffs between tasks in the toolchain can improve DevOps efficiency, software development innovation, and better code quality. Reducing fragmentation enables DevOps and site reliability engineering (SRE) teams to work in a unified way to ensure code quality and security. They need automated DevOps practices.
By leveraging Dynatrace observability on Red Hat OpenShift running on Linux, you can accelerate modernization to hybrid cloud and increase operational efficiencies with greater visibility across the full stack from hardware through application processes. Learn more about the new Kubernetes Experience for Platform Engineering.
Modern solutions like Snyk and Dynatrace offer a way to achieve the speed of modern innovation without sacrificing security. This innovative solution combines Snyk Container and Dynatrace observability data to provide comprehensive reporting—highlighting which running containers have undergone Snyk Container scans.
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.
AI-enabled chatbots can help service teams triage customer issues more efficiently. 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.
To manage these complexities, organizations are turning to AIOps, an approach to IT operations that uses artificial intelligence (AI) to optimize operations, streamline processes, and deliver efficiency. This efficiency translated to a dramatic reduction in the transaction failure rate, from 0.16% to just 0.06%.
Dynatrace recently announced the availability of its latest core innovations for customers running the Dynatrace® platform on Microsoft Azure, including Grail. Transforming business with Azure data analytics In the evolution towards digital and cloud-native solutions, the ability to efficiently manage vast amounts of data is imperative.
As global warming advances, growing IT carbon footprints are pushing energy-efficient computing to the top of many organizations’ priority lists. Energy efficiency is a key reason why organizations are migrating workloads from energy-intensive on-premises environments to more efficient cloud platforms.
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