Posts Tagged devops

Organizations are under constant pressure to deliver new products and features faster than ever. But speed alone isn’t enough—businesses must also navigate the complex challenges of ensuring security and managing infrastructure costs effectively.

Enter DevSecOps - the strategic integration of security practices into the DevOps workflow. By automating security processes, organizations can achieve improved speed, scalability, and business impact, all while ensuring security remains a priority.

Tivity Health, a leading health and fitness solutions provider, has embraced this DevSecOps approach using Pulumi, a modern infrastructure as code (IaC) platform. During PulumiUP 2024, David Giambruno, Tivity Health’s VP of Engineering and DevOps, shared how, by leveraging Pulumi, he led the transformation that continuously drives remarkable results in speed, cost savings, and security.

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Setting up an internal developer platform (IDP) can be a daunting task. There are a lot of tools out there that do some of the work for you, but none of them do all of it. Pulumi P3 is no different. Pulumi Patterns & Practices Platform (P3) is a reference architecture that we will be describing, and providing code for, through this series of articles.

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In 2025, several trends will dominate cloud computing, driving innovation, efficiency, and scalability. From Infrastructure as Code (IaC) to AI/ML, platform engineering to multi-cloud and hybrid strategies, and security practices, let’s explore the 10 biggest emerging trends.

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Infrastructure management is all fun and games until you find yourself scrolling through 1000+ resources in your AWS console. Worse, when one rogue product team wants to use Azure and your data team wants to be on GCP, you’re ARM wrestling in Azure and watching your economies of scale tip the wrong direction as you’re copy-pasting CloudFormation templates into yet another git repo. This. Needs. To. Be. A. Platform!

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We are excited to announce the kickoff of the Platform Engineering & DevOps Series, which will run from July 16 to October 31. This series will feature in-person events across various cities, including Berlin, London, Paris, Sydney, Boston, San Francisco, Seattle, Austin, Denver, and NYC. For those unable to attend an in-person event, we encourage you to participate in a virtual DevOps & Platform Engineering workshop.

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“Developer experience is hard to sell,” said Cleve Littlefield, Engineering Manager at Pulumi, during a casual meeting. With experience as both an end-user developer and a lead in self-service platform implementation, Cleve’s observation stuck with me.

Though I have expertise in leading implementations and upgrades for internal platforms, none were specifically for developers. However, experience remains vital across departments, addressing tools, processes, systems, and best practices, aiming to reduce cognitive load, increase productivity, enhance collaboration, boost communication and much more.

Intriguingly, engineering teams may perceive its value differently. Therefore, we will dive into the concept of developer experience, aka DevEx, which, in truth, should translate into a competitive advantage.

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The integration of artificial intelligence (AI) with DevOps signals a new era in software development. DevOps possesses unique characteristics and needs that make it exceptionally compatible with AI augmentation. Given that code fundamentally relies on language, and large language models (LLMs) serve as the core of GPT functionality, these models are particularly well-suited for tasks such as code generation. This article unwraps the topics addressed during our “AI: Friends or Foe | AI Talks for DevOps” event in San Francisco.

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The emergence of DevOps revolutionized software development. Now, with AI powered tools like LangChain, these transformations are being accelerated. Unsurprisingly, our distinguished speaker at the launch of Pulumi’s in-person AI Talks, Patrick Debois, who coined the term “DevOps,” has recently tuned into LLM and GenAI Ops using the Langchain framework.

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Running models from Hugging Face on Amazon SageMaker is a popular deployment option for AI/ML services. While the SageMaker console allows for provisioning these cloud resources, this deployment pattern is labor intensive to document and vulnerable to human errors when reproducing as a regular operations practice. Infrastructure as Code (IaC) offers a reliable and easy to duplicate deployment practice. By developing this IaC with Pulumi, practitioners can choose to write their infrastructure code in Python and seamlessly develop both AI application code and IaC code in the same language.

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Self-service infrastructure is the holy grail of DevOps. When platform engineering teams can empower application teams to provision their own infrastructure without needing to understand the details of configuring networking, storage, and compute resources, IT organizations can drastically increase their ability to deliver on organizational goals. The first step in this process is to codify infrastructure best practices using platforms like Pulumi and the next step is to make these best practices available in a workflow that fits into the application team’s software development tools and process.

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