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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.
Cloud platforms (AWS, Azure, GCP, etc.) Integrations: Can work across multi-cloud and hybrid-cloud environments, such as AWS, Azure, and Google Cloud Platform, and provide unified visibility and management. If you’re using native Kubernetes, or K8s in AWS EKS, Azure AKS, Google GKE, or on-prem (e.g.
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.
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? Amazon Web Services (AWS). Kubernetes.
What is Azure Functions? Similar to AWS Lambda , Azure Functions is a serverless compute service by Microsoft that can run code in response to predetermined events or conditions (triggers), such as an order arriving on an IoT system, or a specific queue receiving a new message. The growth of Azure cloud computing.
As organizations adopt microservices architecture with cloud-native technologies such as Microsoft Azure , many quickly notice an increase in operational complexity. To guide organizations through their cloud migrations, Microsoft developed the Azure Well-Architected Framework. What is the Azure Well-Architected Framework?
This method of structuring, developing, and operating complex, multi-function software as a collection of smaller independent services is known as microservice architecture. Using a microservices approach, DevOps teams split services into functional APIs instead of shipping applications as one collective unit. Microservices benefits.
This method of structuring, developing, and operating complex, multi-function software as a collection of smaller independent services is known as microservice architecture. Using a microservices approach, DevOps teams split services into functional APIs instead of shipping applications as one collective unit. Microservices benefits.
Many organizations are taking a microservices approach to IT architecture. A microservices approach enables DevOps teams to develop an application as a suite of small services. However, in some cases, an organization may be better suited to another architecture approach. What is the monolithic architecture approach?
As adoption rates for Microsoft Azure continue to skyrocket, Dynatrace is developing a deeper integration with the platform to provide even more value to organizations that run their businesses on Azure or use it as a part of their multi-cloud strategy. Azure Batch. Azure DB for MariaDB. Azure DB for MySQL.
Dynatrace Delivers Most Complete Observability for Multicloud Serverless Architectures. Dynatrace has extended the platform’s deep and broad observability and advanced AIOps capabilities to all major serverless architectures. Dynatrace Advances Application Security with Real-Time Attack Detection and Blocking.
AI-powered automation and deep, broad observability for serverless architectures. In addition to existing support for AWS Lambda , this support now covers Microsoft Azure Functions and Google Cloud Functions as well as managed Kubernetes environments, messaging queues, and cloud databases across all major cloud providers.
To drive better outcomes using hybrid cloud architectures, it helps to understand their benefits—and how to orchestrate them seamlessly. What is hybrid cloud architecture? Hybrid cloud architecture is a computing environment that shares data and applications on a combination of public clouds and on-premises private clouds.
To take full advantage of the scalability, flexibility, and resilience of cloud platforms, organizations need to build or rearchitect applications around a cloud-native architecture. So, what is cloud-native architecture, exactly? What is cloud-native architecture? The principles of cloud-native architecture.
Log monitoring, log analysis, and log analytics are more important than ever as organizations adopt more cloud-native technologies, containers, and microservices-based architectures. Driving this growth is the increasing adoption of hyperscale cloud providers (AWS, Azure, and GCP) and containerized microservices running on Kubernetes.
Leveraging cloud-native technologies like Kubernetes or Red Hat OpenShift in multicloud ecosystems across Amazon Web Services (AWS) , Microsoft Azure, and Google Cloud Platform (GCP) for faster digital transformation introduces a whole host of challenges. They are required to understand the full story of what happened in a system.
Digital workers are now demanding IT support to be more proactive,” is a quote from last year’s Gartner Survey Understandably, a higher number of log sources and exponentially more log lines would overwhelm any DevOps, SRE, or Software Developer working with traditional log monitoring solutions.
As organizations look to expand DevOps maturity, improve operational efficiency, and increase developer velocity, they are embracing platform engineering as a key driver. The pair showed how to track factors including developer velocity, platform adoption, DevOps research and assessment metrics, security, and operational costs.
The goal was to develop a custom solution that enables DevOps and engineering teams to analyze and improve pipeline performance issues and alert on health metrics across CI/CD platforms. Faced with these requirements, Omnilogy carefully evaluated the following two options for implementing a solution to the pipeline observability challenge.
Gone are the days for Christian manually looking at dashboards and metrics after a new build got deployed into a testing or acceptance environment: Integrating Keptn into your existing DevOps tools such as GitLab is just a matter of an API call. Automate Performance aka Performance as a Self-Service: Watch SRE-Driven Performance Engineering.
The fact is, Reliability and Resiliency must be rooted in the architecture of a distributed system. The email walked through how our Dynatrace self-monitoring notified users of the outage but automatically remediated the problem thanks to our platform’s architecture. And that’s true for Dynatrace as well.
According to Forrester Research, the COVID-19 pandemic fueled investment in “hyperscaler public clouds”—Amazon Web Services (AWS), Google Cloud Platform and Microsoft Azure. The session will cover how Dynatrace can help you deliver better software faster as you build applications based on AWS Lambda or microservices architecture.
A service-level objective ( SLO ) is the new contract between business, DevOps, and site reliability engineers (SREs). Example 1: Architecture boundaries. First, they took a big step back and looked at their end-to-end architecture (Figure 2). SLO dashboard defined by architectural boundary. So, what did they do?
Dynatrace enables various teams, such as developers, threat hunters, business analysts, and DevOps, to effortlessly consume advanced log insights within a single platform. DevOps teams operating, maintaining, and troubleshooting Azure, AWS, GCP, or other cloud environments are provided with an app focused on their daily routines and tasks.
Bamboo, AzureDevOps, AWS CodePipeline …. You can also checkout an open source web microservice app and an Azure function app that utilize the Keptn Pitometer Node.js Beyond basic metrics: Detecting Architectural Regressions. Use this to detect any architectural regressions introduced through code or config changes.
As dynamic systems architectures increase in complexity and scale, IT teams face mounting pressure to track and respond to conditions and issues across their multi-cloud environments. Dynatrace news. As teams begin collecting and working with observability data, they are also realizing its benefits to the business, not just IT.
Automatically collect and evaluate business, service, and architectural indicator metrics to promote or roll back deployments. Successful DevOps teams have figured out that “delivering more with less” requires careful management of release risks and automation to scale. SLO validation – ?Automatically Topics in this blog series.
VMware commercialized the idea of virtual machines, and cloud providers embraced the same concept with services like Amazon EC2, Google Compute, and Azure virtual machines. Within this paradigm, it is possible to run entire architectures without touching a traditional virtual server, either locally or in the cloud.
Serverless architecture enables organizations to deliver applications more efficiently without the overhead of on-premises infrastructure, which has revolutionized software development. These tools simply can’t provide the observability needed to keep pace with the growing complexity and dynamism of hybrid and multicloud architecture.
While there isn’t an authoritative definition for the term, it shares its ethos with its predecessor, the DevOps movement in software engineering: by adopting well-defined processes, modern tooling, and automated workflows, we can streamline the process of moving from development to robust production deployments. Software Architecture.
While many companies now enlist public cloud services such as Amazon Web Services, Google Public Cloud, or Microsoft Azure to achieve their business goals, a majority also use hybrid cloud infrastructure to accommodate traditional applications that can’t be easily migrated to public clouds. build microservices-based architecture.
After moving to Microsoft Azure for many of its production-stage applications, Park ‘N Fly’s IT teams experienced blind spots. “We It’s all part of a continuous deployment architecture,” Schirrmacher says. “We To me, AIOps is like having your DevOps people in more automated fashion,” Schirrmacher says.
Spiraling cloud architecture and application costs have driven the need for new approaches to cloud spend. This public cloud management discipline provides IT, DevOps , CloudOps, finance, and business teams with continuous cost optimization tools and accurate accounting of cloud resources. That’s where FinOps can help.
This guest blog is authored by Raphael Pionke , DevOps Engineer at T-Systems MMS. In recent years, customer projects have moved towards complex cloud architectures, including dozens of microservices and different technology stacks which are challenging to develop, maintain, and optimize for resiliency. Dynatrace news. a Jenkinsfile.
If your app runs in a public cloud, such as Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform (GCP), the provider secures the infrastructure, while you’re responsible for security measures within applications and configurations. However, open source software is often a vector for security vulnerabilities.
Software architecture, infrastructure, and operations are each changing rapidly. The shift to cloud native design is transforming both software architecture and infrastructure and operations. Also: infrastructure and operations is trending up, while DevOps is trending down. Coincidence? Probably not, but only time will tell.
The bold ones were building distributed architectures using SOA, trying to implement ESBs and this all looked good on paper but ended up being difficult to implement. . ? Cloud Native DevOps with Kubernetes : . Containers and Microservices: R evolution in the architecture of distributed systems . ? Cloud-native?
The insightful piece featured on InfoQ delves into the intricacies of Azure Functions’ Cold Starts, illuminating a topic frequently stirring debate within the serverless computing sphere.
Each use case provides its own unique value and impact, and whoever sees value in the use cases can adopt it—whether they are a platform engineer, DevOps engineer, performance engineer, or a site reliability engineer (SRE). The various presenters in this session aligned platform engineering use cases with the software development lifecycle.
In particular, achieving observability across all containers controlled by Kubernetes can be laborious for even the most experienced DevOps teams. DevOps and continuous delivery: A revolution in processes, and the way people and software delivery teams work. But what is Kubernetes exactly? Where does it come from? Distributed.
The devil is in the detail, though because of the sheer number, breadth, and volatility of technologies used in modern architectures and the immense volume, velocity, and variety of data they produce. The Hub includes the most prominent platforms like Kubernetes and Red Hat OpenShift as well as public cloud vendors like AWS, GCP, and Azure.
AWS is far and away the cloud leader, followed by Azure (at more than half of share) and Google Cloud. But most Azure and GCP users also use AWS; the reverse isn’t necessarily true. However, close to half (~48%) use Microsoft Azure, and close to one-third (~32%) use Google Cloud Platform (GCP).
And how can you verify this performance consistently across a multicloud environment that also uses Microsoft Azure and Google Cloud Platform frameworks?
That’s why, in part, major cloud providers such as Amazon Web Services, Microsoft Azure, and Google Cloud Platform are discussing cloud optimization. Traditional cloud monitoring methods can no longer scale to meet organizations’ demands, as multicloud architectures continue to expand.
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