Dynatrace

AUGUST 2, 2021

Metrics matter. But without complex analytics to make sense of them in context, metrics are often too raw to be useful on their own. To achieve relevant insights, raw metrics typically need to be processed through filtering, aggregation, or arithmetic operations. Examples of metric calculations.

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Dynatrace

SEPTEMBER 27, 2024

Unrealized optimization potential of business processes due to monitoring gaps Imagine a retail company facing gaps in its business process monitoring due to disparate data sources. Due to separated systems that handle different parts of the process, the view of the process is fragmented.

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Dynatrace

FEBRUARY 2, 2023

This is achieved, in part, by establishing actionable statistical accuracy —not necessarily precise accuracy —through practical levels of metric sampling, aggregation, and extrapolation. Introducing metric extraction from business events Beginning with Dynatrace SaaS version 1.257, you can extract metrics from ingested business events.

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Dynatrace

JUNE 1, 2023

Certain service-level objective examples can help organizations get started on measuring and delivering metrics that matter. Teams can build on these SLO examples to improve application performance and reliability. In this post, I’ll lay out five SLO examples that every DevOps and SRE team should consider.

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Dynatrace

AUGUST 16, 2022

For example: Infrastructure services might provide data about request timings that can give you a precise overview of system health, but the data is logged in a custom format. For example, Dynatrace recently introduced the extraction of log-based metrics for JSON logs. FILTER_OUT(duration < 100).

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Dynatrace

OCTOBER 15, 2021

Loosely defined, observability is the ability to understand what’s happening inside a system from the knowledge of the external data it produces, which are usually logs, metrics, and traces. This information is gathered from remote, often inaccessible points within your ecosystem and processed by some sort of tool or equipment.

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The Netflix TechBlog

NOVEMBER 20, 2023

by Jun He , Yingyi Zhang , and Pawan Dixit Incremental processing is an approach to process new or changed data in workflows. The key advantage is that it only incrementally processes data that are newly added or updated to a dataset, instead of re-processing the complete dataset.

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Dynatrace

DECEMBER 18, 2023

To get a more granular look into telemetry data, many analysts rely on custom metrics using Prometheus. Named after the Greek god who brought fire down from Mount Olympus, Prometheus metrics have been transforming observability since the project’s inception in 2012.

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Dynatrace

OCTOBER 17, 2022

Davis is the causational AI from Dynatrace that processes billions of events and dependencies and constantly analyzes your IT infrastructure. Dynatrace metric events offer the flexibility needed to customize your anomaly detection configuration. Firstly, an anomaly detector known as a metric key analyzes the incoming raw data ingest.

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Dynatrace

MARCH 18, 2021

DevOps metrics and digital experience data are critical to this. Bringing teams together around DevOps metrics made it easier for M&B to identify how it could create better digital experiences for its customers and optimize revenue. Dynatrace news. Beginnings of BizDevOps. Why stop at your own virtual walls?

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Dynatrace

JANUARY 31, 2024

Organizations choose data-driven approaches to maximize the value of their data, achieve better business outcomes, and realize cost savings by improving their products, services, and processes. Data is then dynamically routed into pipelines for further processing. Understanding the context.

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Dynatrace

APRIL 8, 2022

Fluentd is an open-source data collector that unifies log collection, processing, and consumption. It collects, processes, and outputs log files to and from a wide variety of technologies. Processing plugins parse (normalize), filter, enrich (tagging), format, and buffer log streams. Adding the Dynatrace plug-in is easy.

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Dynatrace

MAY 17, 2023

That is, relying on metrics, logs, and traces to understand what software is doing and where it’s running into snags. In addition to tracing, observability also defines two other key concepts, metrics and logs. When software runs in a monolithic stack on on-site servers, observability is manageable enough. What is OpenTelemetry?

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Dynatrace

MAY 7, 2024

Fluent Bit is a telemetry agent designed to receive data (logs, traces, and metrics), process or modify it, and export it to a destination. Fluent Bit and Fluentd were created for the same purpose: collecting and processing logs, traces, and metrics. Observability: Elevating Logs, Metrics, and Traces!

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DZone

JUNE 21, 2023

Monitoring and observability are two key concepts that facilitate this process, offering valuable visibility into the health and performance of systems. In this article, we will explore the differences between monitoring and observability, provide examples to illustrate their applications and highlight their respective benefits.

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Dynatrace

DECEMBER 27, 2022

By implementing service-level objectives, teams can avoid collecting and checking a huge amount of metrics for each service. When organizations implement SLOs, they can improve software development processes and application performance. In this example, “Reverse proxy” and “Front-end server” are clearly in the critical path.

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Dynatrace

JULY 22, 2024

Using OpenTelemetry, developers can collect and process telemetry data from applications, services, and systems. Observability Observability is the ability to determine a system’s health by analyzing the data it generates, such as logs, metrics, and traces. There are three main types of telemetry data: Metrics.

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Latency Best Practices Metrics Open Source 245

Dynatrace

JANUARY 18, 2022

We’ll explore the process of defining SLOs and using the API to scale-out SLOs. The measurement equates to a metric that captures expected results. The first step to defining an SLO is to identify the success metric. Synthetic metrics (Synthetic). Log Metrics (Log). Defining SLIs. Services (Service).

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Dynatrace

MAY 17, 2022

From a cost perspective, internal customers waste valuable time sending tickets to operations teams asking for metrics, logs, and traces to be enabled. A team looking for metrics, traces, and logs no longer needs to file a ticket to get their app monitored in their own environments. The following example drives the point home.

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Scalegrid

JANUARY 25, 2024

You will need to know which monitoring metrics for Redis to watch and a tool to monitor these critical server metrics to ensure its health. Redis returns a big list of database metrics when you run the info command on the Redis shell. You can pick a smart selection of relevant metrics from these.

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Dynatrace

FEBRUARY 21, 2024

Automating quality gates is ideal, as it minimizes manually checking and validating key metrics throughout the SDLC. By actively monitoring metrics such as error rate, success rate, and CPU load, quality gates instill confidence in teams during software releases. Fewer expensive fixes. But how do they function in practice?

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The Netflix TechBlog

FEBRUARY 18, 2022

Event Prioritization Considering the use cases were wide ranging both in terms of their sources and their importance, we built segmentation into the event processing. For example, a member-triggered event such as “ change in a profile’s maturity level” should have a much higher priority than a “ system diagnostic signal”.

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Dynatrace

MAY 6, 2024

A tight integration between Red Hat Ansible Automation Platform, Dynatrace Davis ® AI, and the Dynatrace observability and security platform enables closed-loop remediation to automate the process from: Detecting a problem. With DQL, the workflow trigger to initiate a required automation and remediation process can be defined.

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The Netflix TechBlog

SEPTEMBER 10, 2024

One issue that often complicates this process is the "noisy neighbor" problem. To emit a run queue latency metric, we leveraged three eBPF hooks: sched_wakeup, sched_wakeup_new, and sched_switch. The sched_wakeup and sched_wakeup_new hooks are invoked when a process changes state from 'sleeping' to 'runnable.'

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Dynatrace

NOVEMBER 3, 2021

Monitoring , by textbook definition, is the process of collecting, analyzing, and using information to track a program’s progress toward reaching its objectives and to guide management decisions. Monitoring focuses on watching specific metrics. First, let’s define what we mean by observability and monitoring.

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Dynatrace

AUGUST 10, 2023

But existing business intelligence (BI) tools often lack the broad context, ease of data access, and real-time insights needed to understand and improve customer experience and complex business processes. In both examples, we used Dynatrace OneAgent® deep payload inspection to capture business data in motion.

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Dynatrace

OCTOBER 8, 2020

They may be used to, for example, integrate a new payment service or create a new interface for a booking platform. Full integration with existing Dynatrace capabilities for AWS Lambda (for example, metric ingestion via AWS Cloud Watch). For the Checkout function example (see below), the median response time is around 580ms.

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DZone

JULY 29, 2024

In this post, let’s explore a key performance metric studied during garbage collection analysis: "GC throughput." During that pause period, no customer transactions will be processed. We’ll understand what it means, its significance in Java applications, and how it impacts overall performance.

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The Netflix TechBlog

MAY 4, 2023

The second phase involves migrating the traffic over to the new systems in a manner that mitigates the risk of incidents while continually monitoring and confirming that we are meeting crucial metrics tracked at multiple levels. For example, if some fields in the responses are timestamps, those will differ.

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Dynatrace

MAY 19, 2022

However, many teams struggle with knowing which ones to use and how to incorporate them into the processes. Below, several Dynatrace customers shared their SLO management journey and discussed the resulting dashboards they rely on daily to manage their mission-critical business processes and applications. What are SLOs?

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Dynatrace

OCTOBER 7, 2020

Open-source metric sources automatically map to our Smartscape model for AI analytics. We’ve just enhanced Dynatrace OneAgent with an open metric API. Here’s a quick overview of what you can achieve now that the Dynatrace Software Intelligence Platform has been extended to ingest third-party metrics. Dynatrace news.

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Open Source Metrics Analytics Tuning 261

The Netflix TechBlog

DECEMBER 23, 2020

For example, the PID namespace makes it so that a process can only see PIDs in its own namespace, and therefore cannot send kill signals to random processes on the host. For example, the CAP_SYS_BOOT capability controls the ability of a given user to reboot the machine. Let’s go back to that kernel code example earlier.

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The Netflix TechBlog

JUNE 13, 2023

Replay traffic testing gives us the initial foundation of validation, but as our migration process unfolds, we are met with the need for a carefully controlled migration process. A process that doesn’t just minimize risk, but also facilitates a continuous evaluation of the rollout’s impact.

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Dynatrace

APRIL 28, 2021

Organizations that have transitioned to agile software development strategies (including the adoption of a DevOps culture and continuous delivery automation) enforce automated solutions for such decision making—or at the very least, use automation in the gathering of a release-quality metrics. Each entry represents a process group instance.

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Dynatrace

NOVEMBER 15, 2021

Here’s a look at how two financial institutions are responding to these new business priorities; the details are anonymized to make the examples illustrative, but you may be familiar with some of the challenges. Customer experience has become the brand, bringing IT new opportunities—and challenges. Customer 1: Betting on business KPIs.

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FinTech Metrics Website Monitoring 272

Dynatrace

SEPTEMBER 3, 2020

The second major concern I want to discuss is around the data processing chain. metrics) but it’s just adding another dataset and not solving the problem of cause-and-effect certainty. The four stages of data processing. Four stages of data processing with a costly tool switch.

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Software Software Artificial Intelligence Metrics 264

Dynatrace

JULY 24, 2024

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. Get started monitoring Red Hat OpenShift on IBM Z and LinuxONE New to Dynatrace?

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