Dynatrace

JUNE 13, 2022

Open source code, for example, has generated new threat vectors for attackers to exploit. Cloud operations and observability boost resilience for American Family – blog. Software intelligence as code enables tailored observability, AIOps, and application security at scale – blog.

Open Source 221

Open Source DevOps Java Innovation 221

Dynatrace

AUGUST 5, 2022

RSS feeds are an example of a widely used publish-and-subscribe mechanism. How message queuing benefits microservices. Microservices are an increasingly popular way to build software because of their speed and flexibility compared with traditional monolithic approaches. Watch webinar now! The post What is a message queue?

Monitoring 199

Monitoring Serverless Programming Speed 199

Dynatrace

AUGUST 5, 2022

RSS feeds are an example of a widely used publish-and-subscribe mechanism. How message queuing benefits microservices. Microservices are an increasingly popular way to build software because of their speed and flexibility compared with traditional monolithic approaches. The post What is a message queue?

Monitoring 198

Monitoring Serverless Programming Speed 198

Dynatrace

MAY 24, 2023

Pod and workload overview to quickly identify unexpected differences in application and microservice instances. An example dashboard for Kubernetes workload might look like the following. Here’s an example of a Problem card that Davis opened because of an increased failure rate in the workload called order service.

Azure 226

Azure Monitoring Operating System Virtualization 226

Dynatrace

DECEMBER 9, 2020

Cloud-native technologies and microservice architectures have shifted technical complexity from the source code of services to the interconnections between services. Heterogeneous cloud-native microservice architectures can lead to visibility gaps in distributed traces. Dynatrace news. What’s next?

Java 233

Java Traffic Strategy Architecture 233

Dynatrace

MARCH 27, 2024

This can quickly become overwhelming and hard to manage in today’s complex microservice environments. The automated extraction of ownership information, for example, from Kubernetes annotations, is therefore essential. An example via Monaco can be found in this public GitHub repository.

Best Practices 199

Best Practices Azure Database Code 199

Dynatrace

MAY 23, 2022

As a result, organizations are weighing microservices vs. monolithic architecture to improve software delivery speed and quality. As developers move to microservice-centric designs, components are broken into independent services to be developed, deployed, and maintained separately. Microservices can become complex quickly.

Architecture 194

Architecture DevOps Monitoring Programming 194

Dynatrace

MARCH 27, 2024

Today’s applications are cloud-native, microservices-based, and extend across both the cloud and on-premises servers. It’s an approach that’s particularly powerful when teams use it to, for example, automatically identify patterns of security problems (such as unusual data flows) or find the root causes of issues.

Government 159

Government Network Artificial Intelligence Cloud 159

Dynatrace

APRIL 11, 2023

As organizations migrate applications to the cloud, they must balance the agility that microservices architecture brings with the complexity and lack of transparency that can also come with it. For example, the open source Java library at the heart of the Log4Shell crisis in 2021 was patched within days given the pervasiveness of the code.

Cloud 186

Cloud DevOps Open Source Retail 186

Dynatrace

MAY 23, 2022

Cloud environment toolkits —microservices, Kubernetes, and serverless platforms — deliver business agility, but also create complexity for which many security solutions weren’t designed. Software intelligence as code enables tailored observability, AIOps, and application security at scale – blog. Runtime vulnerability management.

Strategy 224

Strategy Innovation Cloud Serverless 224

Dynatrace

MAY 4, 2021

Today’s highly complex microservices environments require IT operations and SRE teams to observe each service and transaction end-to-end. Now let’s take a closer look at the first two of these scenarios using a concrete example. Dynatrace news. TL;DR summary. This is the root cause of the service failures and user frustration.

Cloud 264

Cloud Java Tuning Monitoring 264

Dynatrace

SEPTEMBER 29, 2021

As businesses break up their monolithic colossuses into nimble containerized microservices, they often reduce time to market from months to days. Think of containers as the packaging for microservices that separate the content from its environment – the underlying operating system and infrastructure. Here are some examples.

Open Source 301

Open Source Traffic DevOps Cloud 301

Dynatrace

DECEMBER 23, 2020

Distributed tracing follows an interaction by tagging it with a unique identifier, which stays with it as it interacts with microservices, containers, and infrastructure. Gaining visibility into monolithic systems before containers, Kubernetes, and microservices was simple. appeared first on Dynatrace blog.

Infrastructure 205

Infrastructure Cloud Monitoring Metrics 205

The Netflix TechBlog

SEPTEMBER 8, 2020

How we migrated our Android endpoints out of a monolith into a new microservice by Rohan Dhruva , Ed Ballot As Android developers, we usually have the luxury of treating our backends as magic boxes running in the cloud, faithfully returning us JSON. In the snippet above, we’re accessing the detail key for the video object with id 80154610.

Latency 233

Latency Cache Java Traffic 233

Dynatrace

NOVEMBER 3, 2021

For example, we can actively watch a single metric for changes that indicate a problem — this is monitoring. For example, when monitoring a database, you’ll want to know about any latency when writing data to a disk or average query response time. True observability, however, relies on more kinds of data than just key indicators.

Monitoring 220

Monitoring Metrics DevOps Scalability 220

The Netflix TechBlog

APRIL 27, 2023

For the example query listed above, the data expressions are name,errors,:eq,:sum and name,rps,:eq,:sum. The internals here are outside the scope of this blog post. The fundamental idea behind Telltale is to detect anomalies on SLI metrics (for example, latency, error rates, etc).

Storage 288

Storage Cache Metrics Database 288

Dynatrace

NOVEMBER 15, 2021

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.

Analytics 208

Analytics Monitoring Artificial Intelligence DevOps 208

The Netflix TechBlog

JANUARY 25, 2023

For example, we have a service that stores a movie entity’s metadata or a service that stores metadata about images. Our team, Asset Management Platform, decided to create a generic service called Marken which allows any microservice at Netflix to annotate their entity. This is a typical use case for a creative review application.

Scalability 283

Scalability Latency Media Architecture 283

Dynatrace

JANUARY 12, 2022

An example of a critical event-based messaging service for many businesses is adding a product to a shopping cart. In serverless and microservices architectures, messaging systems are often used to build asynchronous service-to-service communication. The number of outgoing requests from the queue or topic.

Analytics 186

Analytics Systems DevOps Healthcare 186

Dynatrace

NOVEMBER 18, 2021

Modern heterogeneous stacks consist of countless interconnected and ephemeral components and microservices. Log entries related to individual transactions can be spread across multiple microservices or serverless workloads. The example below includes analysis of a payment issue. This instantly reveals additional context.

Analytics 223

Analytics Cloud Java Serverless 223

Brendan Gregg

MARCH 16, 2024

To explain this example in more detail: The profiler periodically interrupts software execution, and for those disconnected stacks it happens to be the execution of the kernel software ("vfs*", "ext*", etc.). Java, for example, has the -XX:+PreserveFramePointer option. I should do a blog post just on SFrames.

Java 145

Java Cache Google Hardware 145

The Netflix TechBlog

OCTOBER 19, 2020

Netflix member via Twitter This is an example of a question our on-call engineers need to answer to help resolve a member issue?—?which In our previous blog post we introduced Edgar, our troubleshooting tool for streaming sessions. Passing the request context captures causal relationships between microservices during runtime.

Infrastructure 233

Infrastructure Transportation Storage Open Source 233

Dynatrace

DECEMBER 23, 2020

Distributed tracing follows an interaction by tagging it with a unique identifier, which stays with it as it interacts with microservices, containers, and infrastructure. Gaining visibility into monolithic systems before containers, Kubernetes, and microservices was simple. appeared first on Dynatrace blog.

Infrastructure 146

Infrastructure Cloud Monitoring Metrics 146

Dynatrace

FEBRUARY 5, 2020

In Part 1 of this blog series , we presented a few Dynatrace customer use cases for multidimensional analysis. For example, we presented how a multinational travel agency uses MDA to diagnose error rates per loyalty status to make sure that their premium customers have a perfect software experience. Dynatrace news.

Metrics 166

Metrics Code Tuning Monitoring 166

Dynatrace

DECEMBER 22, 2021

They are particularly important in distributed systems, such as microservices architectures. For example, teams can use centralized observability data to improve incident response times, increase automation, and inform critical business decisions. For example, an operation may fail 2% of the time it is performed.

Artificial Intelligence 177

Artificial Intelligence Metrics Architecture DevOps 177

Dynatrace

NOVEMBER 29, 2021

Built on these powerful technologies, OpenShift offers key benefits for software development and container deployment: Run cloud-native microservices at scale. Microservices architecture combines loosely-coupled functions to create high-performing applications. Scale and manage infrastructure. Speeds up development.

Monitoring 147

Monitoring DevOps Infrastructure Metrics 147

Dynatrace

JULY 29, 2021

Today’s digital businesses run on heterogeneous and highly dynamic architectures with interconnected applications and microservices deployed via Kubernetes and other cloud-native platforms. For example, you may need to model physical locations of shops or branch offices due to reporting requirements. Dynatrace news. Next steps.

Analytics 246

Analytics Open Source Serverless Architecture 246

Dynatrace

NOVEMBER 11, 2021

With a growing array of applications, microservices and infrastructure—residing in multiple public and hybrid clouds—many organizations struggle to know where these assets are, how they are performing, and whether they suffer from anomalous or malicious activity.

AWS 212

AWS Cloud Lambda Azure 212

Dynatrace

SEPTEMBER 29, 2021

Part one also provided an overview of Dynatrace’s Cloud Automation solution, Microsoft’s GitHub Actions , and open-source examples you can use and extend related to deployment and release monitoring. For orientation on the use cases in this blog series, refer to the picture below. Blog series use cases. Blog series use cases.

Software 200

Software Software Open Source DevOps 200

Dynatrace

APRIL 10, 2020

Projects that are built on top of Kubernetes (for example, Keptn , Argo , and Istio ) add an extra layer of abstraction and convenience to support teams in their daily work of running and managing the life cycle of applications. This is the most important process because it serves the payment microservice. There’s a Node.js

Cloud 168

Cloud Metrics Availability Technology 168

Dynatrace

JANUARY 23, 2024

For example, high-quality data and predictive AI enable causal AI to provide precise, continuous, and actionable insights in real time. Why growing AI adoption requires an AI observability strategy – blog While AI adoption brings operational efficiency and innovation for organizations, it also introduces the potential for runaway AI costs.

Performance 185

Performance DevOps Innovation Artificial Intelligence 185

Dynatrace

DECEMBER 2, 2021

As organizations adopt microservices-based architecture , service-level objectives (SLOs) have become a vital way for teams to set specific, measurable targets that ensure users are receiving agreed-upon service levels. For example, if your SLO guarantees 99.5% For example, if your SLO is to deliver 99.5% Dynatrace news.

Metrics 190

Metrics Best Practices DevOps Infrastructure 190

Dynatrace

JANUARY 12, 2021

Bringing the analyzed metrics into context with other pillars of observability, for instance traces of microservices within the pod that exposes the metrics. In the following example we chart the redis_commands_duration_seconds_total metric for all Redis pods and split the metric by the dimension cmd. Dynatrace news.

Metrics 178

Metrics Open Source Monitoring Analytics 178

Dynatrace

FEBRUARY 23, 2022

In December of 2021, for example, Log4Shell highlighted the importance of organizations to monitor code in development and production but also the code of their partners and customers. Microservices gain ground over monolithic app development. Microservices go hand-in-hand with serverless computing. and 2.14.1.

Serverless 264

Serverless Infrastructure Innovation DevOps 264

Dynatrace

APRIL 8, 2022

For example, say you find multiple error events in different log files. For example, you can count specific error or alert events and chart them, create Service Level Indicators for SLO tracking, or feed the events back to the Dynatrace Davis AI-engine for refined root-cause analysis. Fluentd logs in context: Example use cases.

Metrics 179

Metrics Analytics Software Architecture Open Source 179

The Netflix TechBlog

MAY 4, 2023

This blog series will examine the tools, techniques, and strategies we have utilized to achieve this goal. The backend for the streaming product utilizes a highly distributed microservices architecture; hence these migrations also happen at different points of the service call graph.

Traffic 339

Traffic Latency Tuning Systems 339

Dynatrace

NOVEMBER 29, 2021

For example, the Dynatrace Data explorer enables you to: Analyze multidimensional metrics, whether built into Dynatrace or ingested from StatsD, Prometheus, Telegraf, and other channels like AWS CloudWatch. The post Dynatrace Support for AWS Lambda Functions Powered by x86 and AWS Graviton2 appeared first on Dynatrace blog.

Lambda 213

Lambda AWS Serverless Metrics 213