This site uses cookies to improve your experience. To help us insure we adhere to various privacy regulations, please select your country/region of residence. If you do not select a country, we will assume you are from the United States. Select your Cookie Settings or view our Privacy Policy and Terms of Use.
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Used for the proper function of the website
Used for monitoring website traffic and interactions
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Strictly Necessary: Used for the proper function of the website
Performance/Analytics: Used for monitoring website traffic and interactions
Leverage AI for proactive protection: AI and contextual analytics are game changers, automating the detection, prevention, and response to threats in real time. UMELT are kept cost-effectively in a massive parallel processing data lakehouse, enabling contextual analytics at petabyte scale, fast.
As a result, organizations are implementing security analytics to manage risk and improve DevSecOps efficiency. Fortunately, CISOs can use security analytics to improve visibility of complex environments and enable proactive protection. What is security analytics? Why is security analytics important? Here’s how.
IT pros want a data and analytics solution that doesn’t require tradeoffs between speed, scale, and cost. With a data and analytics approach that focuses on performance without sacrificing cost, IT pros can gain access to answers that indicate precisely which service just went down and the root cause.
Our latest enhancements to the Dynatrace Dashboards and Notebooks apps make learning DQL optional in your day-to-day work, speeding up your troubleshooting and optimization tasks. These ready-made dashboards offer your platform engineers, who oversee Kubernetes environments, immediate and comprehensive data visibility.
Critical data includes the aircraft’s ICAO identifier , squawk code, flight callsign, position coordinates, altitude, speed, and the time since the last message was received. This information is essential for later advanced analytics and aircraft tracking. Sample JSON data is shown below: Figure 4.
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.
In a digital-first world, site reliability engineers and IT data analysts face numerous challenges with data quality and reliability in their quest for cloud control. Increasingly, organizations seek to address these problems using AI techniques as part of their exploratory data analytics practices. Discovery using global search.
With unified observability and security, organizations can protect their data and avoid tool sprawl with a single platform that delivers AI-driven analytics and intelligent automation. Grail handles data storage, data management, and processes data at massive speed, scale, and cost efficiency,” Singh said.
What is log analytics? Log analytics is the process of viewing, interpreting, and querying log data so developers and IT teams can quickly detect and resolve application and system issues. In what follows, we explore log analytics benefits and challenges, as well as a modern observability approach to log analytics.
What is log analytics? Log analytics is the process of viewing, interpreting, and querying log data so developers and IT teams can quickly detect and resolve application and system issues. In what follows, we explore log analytics benefits and challenges, as well as a modern observability approach to log analytics.
The complexity of such deployments has accelerated with the adoption of emerging, open-source technologies that generate telemetry data, which is exploding in terms of volume, speed, and cardinality. Dynatrace extends its unique topology-based analytics and AIOps approach. For more information visit our web page.
New technologies like Xamarin or React Native are accelerating the speed at which organizations release new features and unlock market reach. How do I connect the dots between mobile analytics and performance monitoring? Connect the dots between mobile analytics and performance monitoring with mobile business analytics.
Mobile analytics can help organizations optimize their mobile application performance, earning customer accolades and increasing revenue in the process. Learn how one Dynatrace customer leveraged mobile analytics to ensure a crash-free, five-star mobile application. Add instrumentation and validate incoming mobile analytics data.
As organizations look to expand DevOps maturity, improve operational efficiency, and increase developer velocity, they are embracing platform engineering as a key driver. Platform engineering: Build for self-service Self-service deployment is a key attribute of platform engineering. “It makes them more productive.
In this post, I wanted to share how I use Google Analytics together with Dynatrace to give me a more complete picture of my customers, and their experience across our digital channels. Google Analytics. Almost all marketers will be familiar with Google Analytics. Digital and Business Analytics. Using Davis, the AI Engine.
Data Engineers of Netflix?—?Interview Interview with Kevin Wylie 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. Kevin Wylie is a Data Engineer on the Content Data Science and Engineering team.
Stream processing enables software engineers to model their applications’ business logic as high-level representations in a directed acyclic graph without explicitly defining a physical execution plan. We designed experimental scenarios inspired by chaos engineering. Chaos scenario: Random pods executing worker instances are deleted.
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.
In this blog, I will be going through a step-by-step guide on how to automate SRE-driven performance engineering. This opens up new analytics use case to e.g: Dynatrace news. Keptn uses SLO definitions to automatically configure Dynatrace or Prometheus alerting rules. detect those test cases that cause high database or CPU overhead.
Every image you hover over isnt just a visual placeholder; its a critical data point that fuels our sophisticated personalization engine. Analytical Insights Additionally, impression history offers insightful information for addressing a number of platform-related analytics queries.
Greenplum Database is an open-source , hardware-agnostic MPP database for analytics, based on PostgreSQL and developed by Pivotal who was later acquired by VMware. This feature-packed database provides powerful and rapid analytics on data that scales up to petabyte volumes. What Exactly is Greenplum? At a glance – TLDR.
For IT infrastructure managers and site reliability engineers, or SREs , logs provide a treasure trove of data. These traditional approaches to log monitoring and log analytics thwart IT teams’ goal to address infrastructure performance problems, security threats, and user experience issues. where an error occurred at the code level.
Grail needs to support security data as well as business analytics data and use cases. With that in mind, Grail needs to achieve three main goals with minimal impact to cost: Cope with and manage an enormous amount of data —both on ingest and analytics. High-performance analytics—no indexing required.
In what follows, we explore some key cloud observability trends in 2023, such as workflow automation and exploratory analytics. From data lakehouse to an analytics platform Traditionally, to gain true business insight, organizations had to make tradeoffs between accessing quality, real-time data and factors such as data storage costs.
The scale and speed of the program triggered challenges for these banks that they had never before imagined. Speed up loan processing to deliver critically needed relief to small businesses? Full speed ahead. Let your Dynatrace Sales Engineer know you want to get started with Digital Business Analytics.
We’re able to help drive speed, take multiple data sources, bring them into a common model and drive those answers at scale.”. As the number of apps and services deployed increases, teams face increased pressure to speed up native mobile app innovation and resolve app issues quicker. Next-gen Infrastructure Monitoring.
In such contexts, platform engineering offers a compelling solution to enable business competitiveness in a manner that significantly enhances the developer experience. Treating an Internal Developer Platform (IDP) as a product is an emerging paradigm within platform engineering communities.
These criteria include operational excellence, security and data privacy, speed to market, and disruptive innovation. With the insights they gained, the team expanded into developing workflow automations using log management and analytics powered by the Grail data lakehouse. This resulted in significant savings and much faster ROI.
Search Engine Optimization Checklist (PDF). Search Engine Optimization Checklist (PDF). Search engine optimization (SEO) is an essential part of a website’s design, and one all too often overlooked. A Smashing Guide To The World Of Search Engine Optimization. by Search Engine Journal. Frederick O’Brien.
An open-source distributed SQL query engine, Trino is widely used for data analytics on distributed data storage. Optimizing Trino to make it faster can help organizations achieve quicker insights and better user experiences, as well as cut costs and improve infrastructure efficiency and scalability. But how do we do that?
Our guide covers AI for effective DevSecOps, converging observability and security, and cybersecurity analytics for threat detection and response. A unified observability and security analytics strategy can guide organizations toward a more proactive security posture at scale. Learn more in this blog.
In what follows, we define software automation as well as software analytics and outline their importance. What is software analytics? This involves big data analytics and applying advanced AI and machine learning techniques, such as causal AI. We also discuss the role of AI for IT operations (AIOps) and more.
For example, it can help DevOps and platform engineering teams write code snippets by drawing on information from software libraries. Engineering teams will, therefore, always need to check the code they get from GPTs to ensure it doesn’t risk software reliability, performance, compliance, or security.
Organizations that miss out on implementing AI risk falling behind their competition in an age where software delivery speed, agility, and security are crucial success factors. By packaging [these capabilities] into hypermodal AI, we are able to run deep custom analytics use cases in sixty seconds or less.”
All of the popular speed testing tools typically provide a page speed score along with their objective results. Google PageSpeed Insights has a their “Speed Score.” While these do have a purpose, most people use them incorrectly, in a way that can be dangerous to your real site speed. seconds to.27 27 seconds!
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.
For example, nearly two-thirds (61%) of technology leaders say they will increase investment in AI over the next 12 months to speed software development. As they continue on this path, organizations expect other benefits , from enabling business users to easily customize dashboards (54%) to building interactive queries for analytics (48%).
By leveraging the AWS Lambda Extensions API , Dynatrace brings the unique value of its Davis AI-engine for fully automatic root cause analysis to AWS Lambda. Serverless functions extend applications to accelerate speed of innovation.
In addition to APM , th is platform offers our customers infrastructure monitoring spanning logs and metrics, digital business analytics, digital experience monitoring, and AIOps capabilities.
Many of these innovations will have a significant analytics component or may even be completely driven by it. For example many of the Internet of Things innovations that we have seen come to life in the past years on AWS all have a significant analytics components to it. Cloud analytics are everywhere.
If you want to get up to speed, check out my recent Performance Clinics: “ AI-Powered Dashboarding ” and “ Advanced Business Dashboarding and Analytics ”. Markdown Usage #1: Adding “Who You Gonna Call” to key Dynatrace dashboards for Help Desk engineers. #2: Dynatrace news. 2: Essential Information for Dynatrace Administrators.
DevSecOps automation DevSecOps automation is a fundamental practice that combines security with the speed and agility of DevOps. This approach helps organizations deliver more secure software and infrastructure with greater efficiency and speed. Download the free 2023 CISO Report.
I never thought I’d write an article in defence of DOMContentLoaded , but here it is… For many, many years now, performance engineers have been making a concerted effort to move away from technical metrics such as Load , and toward more user-facing, UX metrics such as Speed Index or Largest Contentful Paint.
This automatic analysis enables engineers to spend more time innovating and improving business operations. Each piece of the AIOps triumvirate plays a crucial role in the automation process to speed innovation. For example, a typical use case involves a web server running an analytics and reporting system.
We organize all of the trending information in your field so you don't have to. Join 5,000+ users and stay up to date on the latest articles your peers are reading.
You know about us, now we want to get to know you!
Let's personalize your content
Let's get even more personalized
We recognize your account from another site in our network, please click 'Send Email' below to continue with verifying your account and setting a password.
Let's personalize your content