In this New Stack Makers, Codiac aims to simplify app deployment on Kubernetes by offering a unified interface that minimizes complexity. Traditionally, Kubernetes is powerful but challenging for teams due to its intricate configurations and extensive manual coding. Co-founded by Ben Ghazi and Mark Freydl, Codiac provides engineers with infrastructure on demand, container management, and advanced software development life cycle (SDLC) tools, making Kubernetes more accessible.

Codiac’s interface streamlines continuous integration and deployment (CI/CD), reducing deployment steps to a single line of code within CI/CD pipelines. Developers can easily deploy, manage containers, and configure applications without mastering Kubernetes' esoteric syntax. Codiac also offers features like "cabinets" to organize assets across multi-cloud environments and enables repeatable processes through snapshots, making cluster management smoother.

For experienced engineers, Codiac alleviates the burden of manually managing YAML files and configuring multiple services. With ephemeral clusters and repeatable snapshots, Codiac supports scalable, reproducible development workflows, giving engineers a practical way to manage applications and infrastructure seamlessly across complex Kubernetes environments.

Learn more from The New Stack about deploying applications on Kubernetes:

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Three Common Kubernetes Challenges and How to Solve Them 

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Valkey, an open-source fork of Redis launched in March, introduced its multithreaded Version 8.0 in September, now available through AWS ElastiCache. At All Things Open 2024 in Raleigh, AWS's Kyle Davis explains that Valkey was developed after Redis changed to a restrictive license, drawing contributors from companies like AWS, Google, Alibaba, and Oracle. Notably, some contributors emerged independently, including a significant contributor from Vietnam. Version 8.0 differentiates itself from Redis by leveraging multithreaded CPUs, addressing the efficiency of I/O operations in modern hardware. Additionally, data structure refinements were made to improve memory efficiency by up to 20%, particularly benefiting large-key databases.

Looking ahead, Valkey plans two annual updates, with the next release expected in 2025. New modules are anticipated, including a JSON module for efficient data manipulation and a Bloom filter for probabilistic data presence checks. Version 9.0 may bring substantial changes to clustering, updating it to better leverage modern technologies. The Valkey project aims to continue evolving its capabilities to meet the demands of advanced data storage needs.

Learn more from The New Stack about Valkey: 

Valkey Is a Different Kind of Fork 

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Valkey: A Redis Fork With a Future 

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Deb Nicholson, executive director of the Python Software Foundation, attributes Python’s popularity to its minimal syntactical complexity, which appeals to beginners and seasoned developers alike. Python allows flexibility for those exploring coding without a specific focus, unlike purpose-built languages. Since her leadership began in 2022, Nicholson has overseen the foundation’s role in managing Python’s fiscal and operational needs, including the package index that hosts over half a million add-ons. This open ecosystem enables contributions from large corporations and individual developers while demanding vigilant security measures.

Nicholson envisions Python's future advancements, particularly in improving multi-threading and expanding usage in mobile development. She acknowledges Python’s critical role in AI and data science but remains cautious about AI’s pervasive application, likening it to a temporary trend. On open source in the enterprise, Nicholson critiques companies profiting from open-source tools while adopting restrictive licenses. Instead, she admires models like Red Hat’s, which leverage open source sustainably without compromising accessibility or innovation.

Learn more from The New Stack about Python: 

Python 3.13: Blazing New Trails in Performance and Scale

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Python Mulls a Change in Version Numbering

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Platform engineering will be a key focus at KubeCon this year, with a special emphasis on AI platforms. Priyanka Sharma, executive director of the Linux Foundation, highlighted the convergence of platform engineering and AI during an interview on The New Stack Makers with Adobe’s Joseph Sandoval. KubeCon will feature talks from experts like Chen Goldberg of CoreWeave and Aparna Sinha of CapitalOne, showcasing how AI workloads will transform platform operations.

Sandoval emphasized the growing maturity of platform engineering over the past two to three years, now centered on addressing user needs. He also discussed Adobe's collaboration on CNOE, an open-source initiative for internal developer platforms. The intersection of platform engineering, Kubernetes, cloud-native technologies, and AI raises questions about scaling infrastructure management with AI, potentially improving efficiency and reducing toil for roles like SRE and DevOps. Sharma noted that reference architectures, long requested by the CNCF community, will be highlighted at the event, guiding users without dictating solutions. 

Learn more from The New Stack about Kubernetes: 

Cloud Native Networking as Kubernetes Starts Its Second Decade

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How Cloud Foundry Has Evolved With Kubernetes 

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Rohit Choudhary, co-founder and CEO of Acceldata, placed an early bet on data observability, which has proven prescient. In a New Stack Makers podcast episode, Choudhary discussed three key insights that shaped his vision: First, the exponential growth of data in enterprises, further amplified by generative AI and large language models. Second, the rise of a multicloud and multitechnology environment, with a majority of companies adopting hybrid or multiple cloud strategies. Third, a shortage of engineering talent to manage increasingly complex data systems.

As data becomes more essential across industries, challenges in data observability have intensified. Choudhary highlights the complexity of tracking where data is produced, used, and its compliance requirements, especially with the surge in unstructured data. He emphasized that data's operational role in business decisions, marketing, and operations heightens the need for better traceability. Moving forward, traceability and the ability to manage the growing volume of alerts will become areas of hyper-focus for enterprises.

Learn more from The New Stack about data observability: 

What Is Data Observability and Why Does It Matter?

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The Growth of Observability Data Is Out of Control!

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Rust has maintained its place among the top 15 programming languages and has been the most admired language for nine consecutive years. In a New Stack Makers podcast, Joel Marcey, director of technology at the Rust Foundation, discussed the language's growing importance, including initiatives to improve its security, performance, and adoption in various domains. While Rust is widely used in systems and backend programming, it’s also gaining traction in embedded systems, safety-critical applications, game development, and even the Linux kernel.

Marcey highlighted Rust’s strengths as a safe and fast systems language, noting its use on the web through WebAssembly (Wasm), though adoption there is still early. He also addressed Rust vs. Go, explaining that Rust excels in performance-critical applications. Marcey discussed recent updates, such as Rust 1.81, and project goals for 2024, which include a new edition and async improvements.

He also touched on government interest in Rust, including DARPA’s initiative to convert C code to Rust, and the Rust Security Initiative, aimed at maintaining the language’s strong security reputation.

Learn more from The New Stack about Rust 

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In a New Stack Makers episode, Ashley Williams, founder and CEO of axo, highlights how the software world depends on open-source code, which is largely maintained by unpaid volunteers. She likens this to a CVS relying on volunteer-run shipping companies, pointing out how unsettling that might be for customers. The conversation focuses on open-source maintainers’ reluctance to be seen as "suppliers" of software, an idea explored in a 2022 blog post by Thomas Depierre. Many maintainers reject the label, as there is no contractual obligation to support the software they provide. 

Williams critiques the industry's response to this, noting that instead of involving maintainers in software supply chain security, companies have relied on third-party vendors. However, these vendors have no relationship with the maintainers, leading to increased vulnerabilities. Williams advocates for better engagement with maintainers, especially at build time, to improve security. She also reflects on the growing pressures on maintainers and the underappreciation of release teams.

Learn more from The New Stack about open source software supply chain

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The Challenges of Securing the Open Source Supply Chain

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In this New Stack Makers podcast, Xun Wang, CTO of Bloomreach, brings insights from his time at Nvidia, particularly lessons from its founder, Jensen Huang, to his current role in e-commerce personalization. Wang emphasizes structuring organizations to reflect the architecture of the products they build, applying a hands-on, detail-oriented approach that encourages deep understanding of engineering challenges. 

He credits Huang for teaching him the importance of focusing on fundamental architecture rather than relying on iterative testing alone. Wang highlights the impact of generative AI (GenAI) on Bloomreach, explaining how AI-driven search is essential to understanding human language and user intent. As GenAI reshapes application development, Wang stresses the need for engineers to adopt new skills in AI manipulation, while still maintaining traditional coding expertise. He advocates for continuous learning, acknowledging the challenge of staying updated in a rapidly evolving field. Wang, himself, reads extensively to keep pace with innovations, underscoring the importance of staying curious and adaptable in today’s tech landscape. 

Learn more from The New Stack about Entrepreneurship for Engineers: 

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Code reviews can be highly beneficial but tricky to execute well due to the human factors involved, says Adrienne Braganza Tacke, author of *Looks Good to Me: Actionable Advice for Constructive Code Review.* In a recent conversation with *The New Stack*, Tacke identified three challenges teams must address for successful code reviews: ambiguity, subjectivity, and ego.

Ambiguity arises when the goals or expectations for the code are unclear, leading to miscommunication and rework. Tacke emphasizes the need for clarity and explicit communication throughout the review process. Subjectivity, the second challenge, can derail reviews when personal preferences overshadow objective evaluation. Reviewers should justify their suggestions based on technical merit rather than opinion. Finally, ego can get in the way, with developers feeling attached to their code. Both reviewers and submitters must check their egos to foster a constructive dialogue.

Tacke encourages programmers to first review their own work, as self-checks can enhance the quality of the code before it reaches the reviewer. Ultimately, code reviews can improve code quality, mentor developers, and strengthen team knowledge. 

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In the New Stack Makers episode, Adi Polak, Director, Advocacy and Developer Experience Engineering at Confluent discusses the operational and analytical estates in data infrastructure. The operational estate focuses on fast, low-latency event-driven applications, while the analytical estate handles long-running data crunching tasks. Challenges arise due to the "schema evolution" from upstream operational changes impacting downstream analytics, creating complexity for developers. 

Apache Iceberg and Flink help mitigate these issues. Iceberg, a table format developed by Netflix, optimizes querying by managing file relationships within a data lake, reducing processing time and errors. It has been widely adopted by major companies like Airbnb and LinkedIn. 

Apache Flink, a versatile data processing framework, is driving two key trends: shifting some batch processing tasks into stream processing and transitioning microservices into Flink streaming applications. This approach enhances system reliability, lowers latency, and meets customer demands for real-time data, like instant flight status updates. Together, Iceberg and Flink streamline data infrastructure, addressing developer pain points and improving efficiency. 

Learn more from The New Stack about Apache Iceberg and Flink:

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4 Reasons Why Developers Should Use Apache Flink 

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Bob Wise, CEO of Heroku, discussed the impact of generative AI (GenAI) coding tools on software development in a recent episode of The New Stack Makers. He compared the rise of these tools to adding an "infinite number of interns" to development teams, noting that while they accelerate code writing, they don't yet simplify testing, deployment, or production operations. Wise likened this to the early days of Kubernetes, which focused on improving operations rather than the frontend experience. He emphasized that Kubernetes' success was due to its focus on easing the operational burden, something current GenAI tools have yet to achieve.

Heroku, acquired by Salesforce in 2010, is positioned to benefit from these changes by helping teams transition to more automated systems. Wise highlighted Heroku’s strategic bet on Postgres, a database technology that's gaining traction, especially for GenAI workloads. He also discussed Heroku's ongoing migration to Kubernetes, aligning with industry standards to enhance its platform.

Learn more from The New Stack about Heroku

The Data Stack Journey: Lessons from Architecting Stacks at Heroku and Mattermost

Kubernetes and the Next Generation of PaaS 

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