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When first working on a new site-speed engagement, you need to work out quickly where the slowdowns, blindspots, and inefficiencies lie. For example, my site has a homepage, content pages (e.g. I want to be able to form hypotheses and draw conclusions without viewing a single URL or a line of source code.
There’s no async attribute in sight, and the code itself isn’t doing anything special: it’s just injecting a script that resolves to a regular, blocking tag in the DOM: How is this any different to just loading the file normally? For the simplest case, for example: var script = document. The New Syntax. src = ' [link] ' ; document.
Optimize your code by finding and fixing the root cause of garbage collection problems. These details arm you with the knowledge necessary to find the respective code and remove unnecessary allocations. Any significant reduction in allocations will inevitably speed up your code. So what’s going on here?
The IT world is rife with jargon — and “as code” is no exception. “As code” means simplifying complex and time-consuming tasks by automating some, or all, of their processes. Today, the composable nature of code enables skilled IT teams to create and customize automated solutions capable of improving efficiency.
Organizations can customize quality gate criteria to validate technical service-level objectives (SLOs) and business goals, ensuring early detection and resolution of code deficiencies. Ultimately, quality gates safeguard code viability as it advances through the delivery pipeline. But how do they function in practice?
This tool lets you quickly extract typed fields from unstructured text (such as log entries) using the Dynatrace Pattern Language (DPL), enabling you to extract timestamps, determine status codes, identify IP addresses, or work with real JSON objects. This allows you to answer even the most complex questions with ultimate precision.
Segments can implement variables to dynamically provide, for example, a list of entities to users, such as available Kubernetes clusters, for unmatched flexibility and dynamic segmentation. For example, a segment for Service Errors in Azure Region can be applied instantly by selecting it from the dropdown. What are Dynatrace Segments?
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. or 99.99% of the time.
This is a great example of how valuable Dynatrace is for diagnosing performance or scalability issues, and a great testimony that we at Dynatrace use our own product and its various capabilities across our globally distributed systems. And the code-level root cause information is what makes troubleshooting easy for developers.
Key components of GitOps are declarative infrastructure as code, orchestration, and observability. Many observability solutions don’t support an “as code” approach. Dynatrace enables software intelligence as code. Observability is required for effective collaboration and automation.
When Davis detects deviations from this baseline (for example, a sudden dip in usage or a user action that lasts longer than expected), it generates a problem event , identifies the root cause of the problem, and sends notifications based on the configured alerting profile. OneAgent for mobile apps is specific to iOS and Android.
In our specific examples above, the one-big-file pattern incurred 201ms of latency, whereas the many-files approach accumulated 4,362ms by comparison. Connection One thing we haven’t looked at is the impact of network speeds on these outcomes. Compile: the parsed code is compiled into optimised bytecode. That’s almost 22× more!
In order for software development teams to balance speed with quality during the software development cycle (SDLC), development, security, and operations teams (or DevSecOps teams) need to ensure that their practices align with modern cloud environments. That can be difficult when the business climate can prioritize speed.
And by “sample” we mean “an example”, like food samples in your local grocery store. One of the main reasons this feature exists is just like with food samples, to give you “a taste” of the production quality ETL code that you could encounter inside the Netflix data ecosystem. This is one way to build trust with our internal user base.
This is one example of the many use cases we’re exploring. For example, it can help DevOps and platform engineering teams write code snippets by drawing on information from software libraries. It highlights the potential of GPT technology to drive “information democracy” even further.
Annie leads the Chrome Speed Metrics team at Google, which has arguably had the most significant impact on web performance of the past decade. It's really important to acknowledge that none of this would have been possible without the great work from Annie and her small-but-mighty Speed Metrics team at Google. Nice job, everyone!
The DevOps playbook has proven its value for many organizations by improving software development agility, efficiency, and speed. This method known as GitOps would also boost the speed and efficiency of practicing DevOps organizations. Development teams use GitOps to specify their infrastructure requirements in code.
You can, for example, drive ad hoc multidimensional analysis to analyze, chart, and report on microservice-based metrics without code changes. As a simple example, to select the timeframe between 08:00 today and now, just enter 08:00. For example, you can enter last 3 weeks , this month , or previous 2 quarters.
A trivial performance optimisation to help speed up third-party or other-origin requests is to preconnect them: hint that the browser should preemptively open a full connection ( DNS , TCP , TLS ) to the origin in question, for example: In the right circumstances, this simple, single line of HTML can make pages hundreds of milliseconds faster !
Similar to the observability desired for a request being processed by your digital services, it’s necessary to comprehend the metrics, traces, logs, and events associated with a code change from development through to production. Code : The branch for the new feature in a GitHub repository is merged into the main branch.
Here, I want to demonstrate how some of our Dynatrace customers in LATAM are using our platform to adapt, change and improve their processes to confront this unique situation with case study examples from various industries: 1. This is an example of where a low response time is not necessarily a good indicator, this had to be checked.
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. log ( window. performance.
In our increasingly digital world, the speed of innovation is key to business success. Teams are embracing new technologies and continuously deploying code. As a result, e xisting application security approaches can’t keep up with this speed and vari ability of modern development processes. . Dynatrace news.
Tools And Practices To Speed Up The Vue.js Tools And Practices To Speed Up The Vue.js Using the proposed file structure is not a bad way of structuring your project per se, but as your project grows, you will need a better structure as your code becomes clustered and harder to navigate and access files. Development Process.
We also use Micrometer to analyze ingest queue processing speed, which helps us make decisions about adding resources. With these dependencies in place, we can import Micrometer instruments into our example application, as shown in this controller. In these cases, the Dynatrace Operator for Kubernetes provides enrichment as well.
At Perform 2021, Dynatrace product manager Michael Winkler sat down with Atlassian’s DevOps evangelist, Ian Buchanan, to talk about how you can achieve speed, stability, and scale in your DevOps toolchain as you optimize your practices on the path to self-service. The status quo of the DevOps toolchain. Scaling out.
But developers need code-level visibility and code-level data.” That’s not how I envision code-level observability,” Laifenfeld said. Laifenfeld argued that developers shouldn’t bear the burden of the additional workload when their focus is their code: “Learning Kubernetes as a developer is not easy,” she said.
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. For example, 73% of technology leaders are investing in AI to generate insight from observability, security, and business events data.
Further, software development in multicloud environments introduces multiple coding languages and third-party libraries. As a result, these code sources compound opportunities for vulnerabilities to enter the software development lifecycle (SDLC). Ultimately, mature DevSecOps practices may speedcode development rather than block it.
As they increase the speed of product innovation and software development, organizations have an increasing number of applications, microservices and cloud infrastructure to manage. Further, many organizations—more than 90%—have turned to cloud computing to navigate the highwire act of balancing speed and quality.
Cloud-native technologies and microservice architectures have shifted technical complexity from the source code of services to the interconnections between services. Deep-code execution details. You get code-level insights into application code without code changes. Dynatrace news. The app is powered by Kubernetes.
Effective application development requires speed and specificity. Function as a service is a cloud computing model that runs code in small modular pieces, or microservices. In a FaaS model, developers can write code functions on demand, without being hindered by dependencies on existing applications. Dynatrace news.
These frameworks are based on declarative syntax, which allows developers to build native UI for Android and iOS, respectively, with ease and speed. Example user action generated by an app using Jetpack Compose auto-instrumentation. Example user action generated by an app using Jetpack Compose auto-instrumentation.
For example, $ ls -alrth pg_wal/ drwx 3 postgres postgres 68 Dec 7 05:47. The following comments in the PostgreSQL code can tell the whole story. /* * pgarch_readyXlog * * Return name of the oldest xlog file that has not yet been archived. * Let’s first discuss one of the problems that existed in PostgreSQL 14 and older.
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. Example #3 – Automate Monitoring configuration as code. Monitoring as Code workflow example. Blog series use cases.
For example, you might transform the count-based metric “form submissions” into a rate to report form submissions per hour. Examples of metric calculations. Consider the example 75% enrollment-in-autopay goal as an SLO. Here are other examples to spur your imagination: Convert currencies.
For example, users generate user data, ecommerce sites generate business data, and service portals generate service desk tickets and call volume data. IT pros want a data and analytics solution that doesn’t require tradeoffs between speed, scale, and cost. An example is improving customer experience. But it doesn’t stop there.
What Web Designers Can Do To Speed Up Mobile Websites. What Web Designers Can Do To Speed Up Mobile Websites. I recently wrote a blog post for a web designer client about page speed and why it matters. What I didn’t know before writing it was that her agency was struggling to optimize their mobile websites for speed.
For these reasons, as a small engineering team, we’ve found that optimizing for reliability and speed of product delivery is required for us to serve our evolving customers’ needs successfully. You only need to write platform-specific code where it’s necessary, for example, to implement a native UI or when working with platform-specific APIs.
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. In our example, the ADS-B application provides an excellent visual representation for short-term live monitoring purposes.
Part 1 of this series starts will cover the key ingredients needed for successful DevOps use to deliver better software faster, followed by a short overview of GitHub Actions and example use cases related to deployment and release monitoring. Example #1 – Deploy application code to Kubernetes. 2 Confidence: .
Overcoming the barriers presented by legacy security practices that are typically manually intensive and slow, requires a DevSecOps mindset where security is architected and planned from project conception and automated for speed and scale throughout where possible. And this poses a significant risk. Showing a list of key processes.
To compete, organizations have to achieve both speed and reliability when bringing new products and services to market. With CI, multiple software developers can work on different features or modules of the same application and individually commit their updates to a shared code repository as they complete them, often many times a day.
This is easier said than done, so we’ve designed three sets of OKRs examples for software companies to show how it’s possible. In these examples, the product value streams incorporate Flow Metrics into their key results to drive agility and a value focus. Examples of quarterly OKRs for software companies. Activities.
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