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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.
DevOps and security teams managing today’s multicloud architectures and cloud-native applications are facing an avalanche of data. On average, organizations use 10 different tools to monitor applications, infrastructure, and user experiences across these environments.
Over the past decade, DevOps has emerged as a new tech culture and career that marries the rapid iteration desired by software development with the rock-solid stability of the infrastructure operations team. As of August 2019, there are currently over 50,000 LinkedIn DevOps job listings in the United States alone.
Infrastructure as code is a way to automate infrastructure provisioning and management. In this blog, I explore how Dynatrace has made cloud automation attainable—and repeatable—at scale by embracing the principles of infrastructure as code. Infrastructure-as-code. But how does it work in practice?
With the world’s increased reliance on digital services and the organizational pressure on IT teams to innovate faster, the need for DevOps monitoring tools has grown exponentially. But when and how does DevOps monitoring fit into the process? And how do DevOps monitoring tools help teams achieve DevOps efficiency?
But to be scalable, they also need low-code/no-code solutions that don’t require a lot of spin-up or engineering expertise. And operations teams need to forecast cloud infrastructure and compute resource requirements, then automatically provision resources to optimize digital customer experiences.
DevOps automation can help to drive reliability across the SDLC and accelerate time-to-market for software applications and new releases. What is DevOps automation? DevOps automation is a set of tools and technologies that perform routine, repeatable tasks that engineers would otherwise do manually.
DevOps seeks to accomplish smooth and efficient software creation, delivery, monitoring, and improvement by prioritizing agility and adaptability over rigid, stage-by-stage development. What is DevOps? As DevOps pioneer Patrick Debois first described it in 2009, DevOps is not a specific technology, but a tactical approach.
As organizations accelerate innovation to keep pace with digital transformation, DevOps observability is becoming a critical key to success for DevOps and DevSecOps teams. This drive for speed has a cost: 22% of leaders admit they’re under so much pressure to innovate faster that they must sacrifice code quality.
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? A DevOps platform engineer is a more recent term.
Cloud-native environments bring speed and agility to software development and operations (DevOps) practices. So which is it: SRE vs DevOps, or SRE and DevOps? DevOps is focused on optimizing software development and delivery, and SRE is focused on operations processes. DevOps as a philosophy. SRE vs DevOps?
Organizations are increasingly adopting DevOps to stay competitive, innovate faster, and meet customer needs. By helping teams release new software more frequently, DevOps practices are an essential component of digital transformation. Thankfully, DevOps orchestration has evolved to address these problems. What is orchestration?
As organizations mature on their digital transformation journey, they begin to realize that automation – specifically, DevOps automation – is critical for rapid software delivery and reliable applications. In turn, manual approaches to identifying code issues and troubleshooting are not scalable. This statistic is despite the $9.1
DevOps and platform engineering are essential disciplines that provide immense value in the realm of cloud-native technology and software delivery. Observability of applications and infrastructure serves as a critical foundation for DevOps and platform engineering, offering a comprehensive view into system performance and behavior.
You have set up a DevOps practice. As we look at today’s applications, microservices, and DevOps teams, we see leaders are tasked with supporting complex distributed applications using new technologies spread across systems in multiple locations. DevOps metrics to help you meet your DevOps goals. Dynatrace news.
HashiCorp’s Terraform is an open-source infrastructure as a code software tool that provides a consistent CLI workflow to manage hundreds of cloud services. Per HashiCorp, this codification allows infrastructure changes to be automated while keeping the definition human readable. What is monitoring as code?
More than 90% of enterprises now rely on a hybrid cloud infrastructure to deliver innovative digital services and capture new markets. That’s because cloud platforms offer flexibility and extensibility for an organization’s existing infrastructure. Dynatrace news. With public clouds, multiple organizations share resources.
To accomplish this, organizations have widely adopted DevOps , which encompasses significant changes to team culture, operations, and the tools used throughout the continuous development lifecycle. Key components of GitOps are declarative infrastructure as code, orchestration, and observability.
Many organizations that have integrated their software development and operations into DevOps practices struggle with efficiency because they’re juggling disparate DevOps tools, or their tools aren’t meeting their needs. The status quo of the DevOps toolchain. How to approach transforming your DevOps processes.
Protecting IT infrastructure, applications, and data requires that you understand security weaknesses attackers can exploit. Examples of such weaknesses are errors in application code, misconfigured network devices, and overly permissive access controls in a database. Dynatrace news. How does vulnerability assessment work?
That’s especially true of the DevOps teams who must drive digital-fueled sustainable growth. All of these factors challenge DevOps maturity. Data scale and silos present challenges to DevOps maturity DevOps teams often run into problems trying to drive better data-driven decisions with observability and security data.
The DevOps approach to developing software aims to speed applications into production by releasing small builds frequently as code evolves. As part of the continuous cycle of progressive delivery, DevOps teams are also adopting shift-left and shift-right principles to ensure software quality in these dynamic environments.
The DevOps approach to developing software aims to speed applications into production by releasing small builds frequently as code evolves. As part of the continuous cycle of progressive delivery, DevOps teams are also adopting shift-left and shift-right principles to ensure software quality in these dynamic environments.
In the world of DevOps and SRE, DevOps automation answers the undeniable need for efficiency and scalability. Though the industry champions observability as a vital component, it’s become clear that teams need more than data on dashboards to overcome persistent DevOps challenges.
If you’re doing it right, cloud represents a fundamental change in how you build, deliver and operate your applications and infrastructure. And that includes infrastructure monitoring. This also implies a fundamental change to the role of infrastructure and operations teams. Able to provide answers, not just data.
DevOps and site reliability engineering (SRE) teams aim to deliver software faster and with higher quality. What these steps have in common is that monitoring tools are not in sync with new changes in code or topology and this observability data is often siloed within different tools and teams. The role of observability within DevOps.
Artisan Crafted Images In the Netflix full cycle DevOps culture the team responsible for building a service is also responsible for deploying, testing, infrastructure, and operation of that service. We now have the software and instance configuration as code.
As the new standard of monitoring, observability enables I&O, DevOps, and SRE teams alike to gain critical insights into the performance of today’s complex cloud-native environments. Observability defined. The case for observability. The architects and developers who create the software must design it to be observed.
And, this is even more apparent due to the ever-increasing infrastructure complexity enterprises are dealing with. At Dynatrace we believe that monitoring and performance should both be automated processes that can be treated as code without the need for any manual intervention. Benefits of Everything as Code.
Service-level objectives (SLOs) are a great tool to align business goals with the technical goals that drive DevOps (Speed of Delivery) and Site Reliability Engineering (SRE) (Ensuring Production Resiliency). Creating an SLO dashboard for Business, DevOps, and SREs. Dynatrace news. This capability was nicely explained in a recent blog.
Endpoints include on-premises servers, Kubernetes infrastructure, cloud-hosted infrastructure and services, and open-source technologies. Observability across the full technology stack gives teams comprehensive, real-time insight into the behavior, performance, and health of applications and their underlying infrastructure.
The DevOps playbook has proven its value for many organizations by improving software development agility, efficiency, and speed. These methods improve the software development lifecycle (SDLC), but what if infrastructure deployment and management could also benefit? It is scalable and reduces time needed to set up infrastructure.
The development of internal platform teams has taken off in the last three years, primarily in response to the challenges inherent in scaling modern, containerized IT infrastructures. The ability to effectively manage multi-cluster infrastructure is critical to consistent and scalable service delivery.
Indeed, according to one survey, DevOps practices have led to 60% of developers releasing code twice as quickly. But increased speed creates a tradeoff: According to another study, nearly half of organizations consciously deploy vulnerable code because of time pressure. Increased adoption of Infrastructure as code (IaC).
A platform encompasses a set of tools, services, and infrastructure that enables developers to build, test, and deploy software applications. Other aspects of the discipline — such as infrastructure as code, automation, and standardization — reduce extraneous manual processes to increase developer productivity.
This modular microservices-based approach to computing decouples applications from the underlying infrastructure to provide greater flexibility and durability, while enabling developers to build and update these applications faster and with less risk. And if you don’t own the code for a specific service, you lose end-to-end visibility.
Navigate digital infrastructure complexity In today’s rapidly evolving digital environment, organizations face increasing pressure from customers and competitors to deliver faster, more secure innovations. The effectiveness of this automation relies on the quality of the underlying data.
As organizations look to expand DevOps maturity, improve operational efficiency, and increase developer velocity, they are embracing platform engineering as a key driver. The goal is to abstract away the underlying infrastructure’s complexities while providing a streamlined and standardized environment for development teams.
As organizations become cloud-native and their environments more complex, DevOps teams are adapting to new challenges. Today, the platform engineer role is gaining speed as the newest byproduct of scaling DevOps in the emerging but complex cloud-native world. What is this new discipline, and is it a game-changer or just hype?
Today, speed and DevOps automation are critical to innovating faster, and platform engineering has emerged as an answer to some of the most significant challenges DevOps teams are facing. Everything as code: GitOps as the standard Observability as code is used to programmatically define observability and security.
In the coming weeks and months, we will add to the current collection of templates for synthetic monitoring, digital experience management measures, Kubernetes resource optimization, and infrastructure monitoring. At the same time, dedicated configuration-as-code support in Monaco and Terraform will provide a scalable, automated solution.
For example, it can help DevOps and platform engineering teams write code snippets by drawing on information from software libraries. First, SREs must ensure teams recognize intellectual property (IP) rights on any code shared by and with GPTs and other generative AI, including copyrighted, trademarked, or patented content.
DevSecOps is a cross-team collaboration framework that integrates security into DevOps processes from the start rather than waiting to address security in a separate silo. How is it different from DevOps, and what’s next for the relationship between development, security, and operations within enterprises?
Think of containers as the packaging for microservices that separate the content from its environment – the underlying operating system and infrastructure. The time and effort saved with testing and deployment are a game-changer for DevOps. In production, containers are easy to replicate.
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