# backend-development Published articles for backend-development. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Frontend vs Backend Explained for Beginners 2026 DevFeed: [Frontend vs Backend Explained for Beginners 2026]() Original publisher: [Read original article]() Author: Ekakshar Published: 2026-11-05T10:22:21Z Content type: article Language: en Sources: [Talent500]() Topics: [Back end](), [Front end](), [Web Development](), [Learning](), [Full Stack Development](), [backend frameworks](), [Programming](), [Web Accessibility (a11y)](), [Tool](), [performance-optimization](), [Node.js](), [Vite]() Tags: [2026](), [api](), [api-design](), [api-development](), [backend](), [backend-developer-skills](), [backend-development](), [beginners](), [career](), [development](), [frameworks](), [frontend](), [frontend-and-backend-frameworks](), [frontend-and-backend-programming-languages](), [frontend-developer-skills](), [frontend-development](), [frontend-vs-backend](), [frontend-vs-backend-explained-for-beginners-2026](), [full-stack-development](), [languages](), [programming](), [programming-languages](), [roles](), [tools](), [web](), [web-development](), [web-development-career-paths]() ### AI overview Frontend development builds the interface people see and use, typically with HTML, CSS, and JavaScript; backend development processes requests, manages data and business rules, and enforces security on servers through APIs and databases. They work together: the frontend sends input to backend services and presents their responses. Browser-side checks can improve usability, but sensitive validation and permissions must be enforced by the backend because client code can be bypassed. The article recommends starting with the area that best matches your interests: interface design and interaction for frontend, or logic, data, and system behavior for backend. Learn one area deeply before expanding; basic knowledge of the other helps collaboration, and full-stack work adds breadth. It lists example stacks and skills, while noting that hiring demand varies by region and employer and neither path guarantees an easier first job. ### Source excerpt Confused about Frontend vs Backend development? Understand how these two sides of web development work together to create functional websites and applications. Explore their roles, programming languages, frameworks, tools, key differences, and career paths to find where your interests fit best. The post Frontend vs Backend Explained for Beginners 2026 appeared first on Talent500 blog. ## AI agents need to be replaceable - without losing your work DevFeed: [AI agents need to be replaceable - without losing your work]() Original publisher: [Read original article]() Author: Manveer Chawla Published: 2026-10-28T13:00:00Z Content type: article Language: en Sources: [The New Stack]() Topics: [long-running](), [reliability-engineering](), [Transactions](), [API](), [OpenTelemetry](), [API Logging](), [Langgraph]() Tags: [agents](), [ai](), [ai-agents](), [ai-engineering](), [api](), [backend-development](), [cdc](), [clickhouse](), [durable-execution](), [idempotency](), [langfuse](), [payment](), [post-contributed](), [sponsor-clickhouse](), [sponsored-post-contributed]() ### AI overview Make the business operation outlive the agent: before dispatch, commit an authoritative record containing the approved parameters, authorization, provider idempotency key, operation ID, and status. A replacement agent retrieves that record and the tool boundary validates requests against it, so the agent cannot redefine the approved action. LangGraph and Temporal can resume execution, but they cannot determine whether an external side effect completed; retries with the original idempotency key can help prevent duplicate operations. Langfuse traces and ClickStack events can narrow the failure window, but neither proves the provider committed the refund, and asynchronously sent traces may be missing. The provider remains authoritative. Follow an application-defined recovery protocol: confirm completion, wait if pending, retry only after definitive failure and revalidation, and escalate unresolved outcomes. Recheck current conditions and authorization before acting. ### Source excerpt An agent receives approval to process a partial refund. It sends the request to a payment API, and the process The post AI agents need to be replaceable - without losing your work appeared first on The New Stack. ## When GraphQL earns its place in an enterprise application, and when it doesn't DevFeed: [When GraphQL earns its place in an enterprise application, and when it doesn't]() Original publisher: [Read original article]() Author: Vaishnavi Khosla Published: 2026-10-27T09:00:00Z Content type: article Language: en Sources: [InfoWorld]() Topics: [GraphQL](), [REST API](), [Back end](), [business logic]() Tags: [access-control](), [api](), [application](), [authorization](), [back-end](), [backend](), [backend-development](), [connected-data](), [contributor](), [costs](), [data](), [data-management](), [data-management-development-approaches-development-tools-software-development](), [development-approaches](), [development-tools](), [enterprise](), [fields](), [front-end](), [governance](), [graphql](), [it](), [language-en](), [query](), [rest](), [rest-api](), [screen](), [software-development](), [storytype-opinion]() ### AI overview GraphQL is most useful when screens need different slices of highly interconnected data: a client can request related objects in one query, reducing sequential REST calls and the need to build new tailored endpoints as screens change. The author's access-governance example has this pattern, while noting the benefit is fewer endpoints and queries rather than a quantified time saving. The tradeoffs are harder caching, potentially expensive deep or broad queries, and authorization checks at object and field level. The text recommends query depth and cost limits, pagination, and keeping authorization rules in shared business logic rather than resolvers. Adoption depends on varied client needs, data interdependence, schema ownership, and centralized authorization; a read-heavy screen is suggested as a trial when answers are mixed. REST remains the author's choice for command operations such as credential rotation, which benefit from focused authorization, logging, and retries. ### Source excerpt The value of GraphQL emerges for a specific type of enterprise screen, one that brings together highly interdependent data across multiple sources. In all other cases, there is a price to pay, which is bound to come out after you have already made the decision. I build internal access-governance applications, with React front ends that talk to both REST and GraphQL back ends. Using the two side by side has shown me where each earns its keep and where each gets in the way. The article is divided into three sections. The first section covers areas in which GraphQL eliminates round trips and front-end work. The second section highlights the underestimated costs involved. Finally, there are a few questions you can ask yourself before implementing the GraphQL approach. GraphQL helps most on screens built from connected data Imagine the details screen for one client. On this screen, you see the client, his/her accounts, permissions for these accounts, owners of these accounts and some related objects for each. Data is highly interrelated, and your screen requires some portion of each layer at once. There are two scenarios for working with REST API. In the first scenario, the front end makes several requests - first for the client, then for his accounts and then for permissions of each of those accounts. Each request in the chain waits for the preceding request to be finished. Another scenario is when the back end creates a specific endpoint in the desired format. The first one becomes very inefficient whenever the network has some issues. The second one works well as long as the information that is to appear on the next screen appears in the same format as before, but then you get many endpoints nobody cares about maintaining. With the help of GraphQL, it becomes possible to change the decision-maker of the shape. The client asks for the query with the specific fields and receives the response in the specific format. This is how it is described in the GraphQL documentatio ## Agent Graph Engineering, Part 3: Why Your WebSocket Clients Need Generated Types DevFeed: [Agent Graph Engineering, Part 3: Why Your WebSocket Clients Need Generated Types]() Original publisher: [Read original article]() Author: Huy Nguyen Published: 2026-10-22T08:21:23Z Content type: article Language: en Sources: [HackerNoon]() Topics: [WebSocket](), [union types]() Tags: [agent](), [ai-agent](), [ai-agent-safety](), [architecture](), [backend-development](), [cross-language-types](), [graph](), [python](), [services](), [types](), [typescript](), [websocket]() ### AI overview The article argues that when services cross process or language boundaries, declare data shapes on the server and generate clients and interfaces from those contracts. OpenAPI supplies a typed REST client; AsyncAPI carries WebSocket event types and directionality into TypeScript, so adding or removing an event updates the generated union and can expose stale frontend handling at compile time. Tool argument schemas can also drive approval forms, validation, and defaults, helping ensure reviewers see the fields the server accepts. The approach adds build and regeneration steps, may require a live schema endpoint, and inherits generator choices; the article says it brings little value for one service in one language or throwaway prototypes, while public APIs still need versioning. ### Source excerpt Three services in two languages means three seams, and a hand-maintained seam is a slow leak. ## One Rogue pip install Away from a Breach DevFeed: [One Rogue pip install Away from a Breach]() Original publisher: [Read original article]() Author: Himashi Meththasena Published: 2026-10-21T19:52:57Z Content type: article Language: en Sources: [HackerNoon]() Topics: [supply-chain-security](), [pip](), [CI/CD]() Tags: [2026](), [attacks](), [audit](), [automate](), [automated](), [automatically](), [backend-development](), [breach](), [ci-cd](), [ci-cd-pipeline](), [ci-cd-security](), [cryptographic](), [cryptographic-verification](), [cves](), [dependencies](), [dependency](), [install](), [pip](), [pip-install](), [python](), [python-programming](), [rogue](), [secure-infrastructure](), [secure-software-development](), [software-development](), [software-engineering](), [supply-chain]() ### AI overview The excerpt recommends deterministic Python dependency installs to reduce exposure to compromised or altered packages. It contrasts pip-tools, which compiles abstract requirements into a pinned, hash-checked requirements.txt, with Poetry, which manages environments and dependencies through a lockfile covering direct and transitive packages. For production installs, it shows pip --require-hashes rejecting packages whose hashes differ from the locked configuration. It also recommends adding pip-audit or Safety scans to CI/CD; pip-audit checks locked versions against vulnerability databases. These steps address version drift, package integrity, and known vulnerabilities, though the excerpt does not establish that they prevent every supply-chain attack. ### Source excerpt Stop Using pip Install Blindly: Securing Your Python Supply Chain in 2026 ## Demystifying Python Asyncio: When to Use Concurrency vs. Multiprocessing in Production. DevFeed: [Demystifying Python Asyncio: When to Use Concurrency vs. Multiprocessing in Production.]() Original publisher: [Read original article]() Author: Himashi Meththasena Published: 2026-10-18T12:09:36Z Content type: tutorial Language: en Sources: [HackerNoon]() Topics: [Python](), [Distributed Systems & Parallel Computing](), [Production Engineering]() Tags: [api](), [asynchronous-performance](), [asyncio](), [backend-development](), [concurrency](), [contest-tags](), [fastapi](), [multiprocessing](), [multiprocessing-in-programming](), [performance](), [python](), [python-programming](), [software-development](), [software-engineering]() ### AI overview The tutorial explains how to choose between Python asyncio concurrency for I/O-bound work and multiprocessing for CPU-bound work, including the effects of the Global Interpreter Lock and ways to keep blocking tasks from stalling web services. ### Source excerpt Learn when to use Python asyncio, threading, or multiprocessing to improve API performance, handle I/O efficiently, and scale CPU-intensive workloads. ## Here are the engineering lessons we learned when live-streaming sports to 32 million people DevFeed: [Here are the engineering lessons we learned when live-streaming sports to 32 million people]() Original publisher: [Read original article]() Author: Cynthia Dunlop Published: 2026-10-17T16:00:00Z Content type: article Language: en Sources: [The New Stack]() Topics: [Production Engineering](), [Software Engineering](), [Chaos Engineering](), [data streams monitoring]() Tags: [backend-development](), [data-streaming](), [engineering](), [live-streaming](), [post-contributed](), [scylladb](), [software-testing](), [sponsor-scylladb](), [sponsored-post-contributed](), [sports]() ### AI overview An engineering team prepared JioHotstar's streaming platform for an IPL final that drew 32 million concurrent viewers. The article describes capacity planning, critical path reviews, partner and system load testing, failure mitigation, and latency budgets, then offers guidance for preparing systems and teams for high-uncertainty events. ### Source excerpt Live sports involve myriad unknowns, but one thing is certain: the live video feed must play flawlessly, and simultaneously, for The post Here are the engineering lessons we learned when live-streaming sports to 32 million people appeared first on The New Stack. ## You can outgrow vanilla Postgres without abandoning Postgres DevFeed: [You can outgrow vanilla Postgres without abandoning Postgres]() Original publisher: [Read original article]() Author: Kimberly Fessel Published: 2026-10-08T16:23:19Z Content type: article Language: en Sources: [The New Stack]() Topics: [sql-database](), [Prisma]() Tags: [ai-engineering](), [backend-development](), [columnar](), [data](), [database](), [database-migration](), [databases](), [databricks](), [developer](), [engineering](), [indexes](), [lakebase](), [live-data](), [optimize](), [postgres](), [sponsor-tiger-data](), [sponsored](), [sponsored-webinar](), [tiger-data](), [webinar]() ### AI overview The document promotes an October 21 webinar about how growing live-data workloads can strain vanilla Postgres and possible ways to respond. It describes query optimization, partitioning, autovacuum tuning, and index maintenance, then presents TimescaleDB and Databricks Lakebase as approaches to scaling while retaining Postgres. ### Source excerpt For many data aficionados, Postgres is the way to store and manage relational data. It's efficient, it's straightforward, and it The post You can outgrow vanilla Postgres without abandoning Postgres appeared first on The New Stack. ## Designing Recoverable Background Workflows With Explicit Execution History DevFeed: [Designing Recoverable Background Workflows With Explicit Execution History]() Original publisher: [Read original article]() Author: Vitaly Raideria Published: 2026-10-05T11:44:20Z Content type: tutorial Language: en Sources: [HackerNoon]() Topics: [execution](), [Error Handling](), [CI/CD]() Tags: [backend-development](), [capacity-planning](), [dagychu](), [data-engineering](), [distributed-systems](), [failure-recovery](), [pipeline](), [recovery](), [self-hosted-software](), [workflow-automation](), [workflow-orchestration](), [workflows]() ### AI overview This tutorial explains how explicit pipeline dependencies and execution history can help operators diagnose failed background workflows and choose a recovery point. Using Dagychu and an illustrative reporting pipeline, it covers job boundaries, reruns, retries, side effects, and self-hosting responsibilities. ### Source excerpt A failed pipeline doesn't always need a full restart. Learn how execution history, dependencies and side effects determine the safest recovery point. ## A Practical Guide to Automated Testing in Backend Systems DevFeed: [A Practical Guide to Automated Testing in Backend Systems]() Original publisher: [Read original article]() Author: Mehrad Published: 2026-10-02T14:45:46Z Content type: tutorial Language: en Sources: [HackerNoon]() Topics: [Software Engineering](), [Integration testing](), [Fuzzing/Fuzz testing](), [mutation-testing](), [Test automation](), [Unit testing]() Tags: [automated-testing](), [backend](), [backend-development](), [e2e](), [end-to-end-testing](), [feature-testing](), [fuzz-testing](), [guide](), [integration](), [integration-testing](), [property-based-testing](), [testing](), [unit-testing]() ### AI overview This guide explains how to choose backend tests based on the risks they cover and their cost. It describes unit, integration, feature, contract, end-to-end, characterization, property-based, fuzz, mutation, performance, smoke, and regression testing, with examples and trade-offs. It also discusses test maintenance, coverage, feedback speed, and balancing a test suite. ### Source excerpt A professional guide to Backend Automated Testing, covering Unit, Integration, Feature, Contract, E2E, Characterization, and Performance Testing. ## The Hidden Truth About File Deletion: Docker, MinIO, and Storage Layers Explained DevFeed: [The Hidden Truth About File Deletion: Docker, MinIO, and Storage Layers Explained]() Original publisher: [Read original article]() Author: Has San Published: 2026-09-30T12:09:54Z Content type: article Language: en Sources: [DevOps.dev]() Topics: [MinIO](), [Data Recovery](), [file](), [container images]() Tags: [api](), [backend-development](), [block](), [data](), [delete](), [docker](), [file](), [filesystem](), [forensic](), [index](), [layers](), [minio](), [object](), [programming](), [recovery](), [software-development](), [storage](), [volumes]() ### AI overview Deletion usually removes a reference or hides data from a namespace, while physical bytes may remain until the storage layer reuses or reclaims them. On HDDs, freed blocks can sometimes be recovered before reuse; SSD TRIM marks pages reclaimable, with cleanup handled later by garbage collection. In Docker, deleting a file in a container's writable layer hides it through OverlayFS, while removing a container leaves its volumes intact; named volumes require separate removal. MinIO object deletion removes an object from the bucket view, but storage cleanup depends on its engine. With bucket versioning enabled, a delete may add a marker while prior versions remain, requiring explicit version deletion or a lifecycle policy. The article also notes that PostgreSQL space may await VACUUM and Git history retains removed files in earlier commits. ### Source excerpt The Hidden Truth About File Deletion: Docker, MinIO, and Storage Layers Explained I assumed for a long time that delete meant gone. Like, actually gone -- bytes wiped, storage reclaimed, done. It doesn't work that way. And once I understood what actually happens at the storage layer, a bunch of confusing behavior I'd run into with Docker volumes and MinIO suddenly made sense. A file isn't one thing Take report.pdf. It looks like a single object on your disk. It's not. The filesystem splits it into three separate concepts: Directory entry: "report.pdf" ↓ Metadata (size, permissions, timestamps) ↓ Pointers to blocks: [102, 103, 104] ↓ Block 102: [bytes] Block 103: [bytes] Block 104: [bytes] The filename is a label. It points to metadata. The metadata points to where the actual bytes live. Three layers, not one. This matters the moment you delete. What rm actually doesrm report.pdf The filesystem: Removes the directory entry Marks blocks 102, 103, 104 as available Moves on That's it. It doesn't overwrite anything. The bytes are still physically on disk -- they're just not indexed anymore. Block 102: [old PDF bytes] -> marked FREE Block 103: [old PDF bytes] -> marked FREE Block 104: [old PDF bytes] -> marked FREE Think of it like tearing the table of contents out of a book. The pages are still there. You just can't find them easily anymore. Why deleted files can be recovered Recovery tools don't use the filesystem index. They scan raw disk blocks looking for recognizable file signatures. PDFs start with %PDF. ZIPs start with PK. If the blocks haven't been reused yet, the data is often intact. This is how forensic recovery works. And it's why deleting a sensitive file isn't enough if you actually need it gone: shred -u report.pdf shred overwrites the blocks multiple times before removing the directory entry. Much harder to recover after that. The blocks eventually get overwritten anyway when new files need space. But "eventually" could be minutes or months depending on how bu ## Agents can now set up your website's security with Turnstile Spin DevFeed: [Agents can now set up your website's security with Turnstile Spin]() Original publisher: [Read original article]() Author: Jules Lemee Published: 2026-09-25T13:00:00Z Content type: release Language: en Sources: [Cloudflare Blog]() Topics: [Cloudflare](), [Security](), [AI-assisted coding](), [Website](), [API](), [Back end](), [Front end](), [Users]() Tags: [agents](), [ai](), [ai-coding-agent](), [backend-development](), [bot-management](), [captcha](), [captchas](), [cloudflare](), [code](), [engineering](), [security](), [turnstile]() ### AI overview Cloudflare announces Turnstile Spin, an agent-mediated implementation that creates and embeds Turnstile widgets, adds Siteverify validation to backend functions, fixes incomplete installations, and supports migrations from other CAPTCHA providers. ### Source excerpt Misconfiguring Turnstile by skipping backend validation leaves sites exposed to bots. Turnstile Spin fixes incomplete setups by using your preferred AI coding agent to wire up server-side verification. ## What Jobs Can You Get After Learning Python? 6 Careers and Their Salaries DevFeed: [What Jobs Can You Get After Learning Python? 6 Careers and Their Salaries]() Original publisher: [Read original article]() Author: Kari Brooks Published: 2026-08-10T20:00:19Z Content type: article Language: en Sources: [Treehouse]() Topics: [Python](), [Learning](), [Machine learning](), [Artificial Intelligence]() Tags: [2026](), [ai](), [analyst](), [artificial-intelligence](), [automation](), [backend](), [backend-development](), [beginner](), [beginners](), [blog](), [career-advice](), [career-change](), [careers](), [data](), [data-analyst](), [data-scientist](), [jobs](), [learn](), [learn-to-code](), [learning](), [post](), [python](), [python-careers](), [salaries](), [tech-jobs](), [web](), [welcome]() ### AI overview Python can lead to several tech careers, but the excerpt describes different experience requirements across the paths. Data analyst is presented as the most beginner-friendly option, using pandas to clean data and turn findings into decisions. Backend development, with frameworks such as Django or Flask, is described as a solid entry point for people who enjoy building applications. Data science generally also calls for statistics, basic machine learning, SQL, and experience or a strong project portfolio. Machine learning engineering is characterized as senior-leaning and requiring strong Python, math, and software engineering skills to put models into scalable products. Automation engineering uses scripts to remove repetitive tasks, though the excerpt ends before giving more detail. The opening gives a broad salary range, from roughly $60,000 for entry-level analysts to over $180,000 for senior ML engineers, without role-by-role figures. ### Source excerpt Python opens doors to data, web, AI, and automation careers. Here are six real jobs you can land after learning Python, what they pay, and which ones welcome beginners. The post What Jobs Can You Get After Learning Python? 6 Careers and Their Salaries appeared first on Treehouse Blog. ## From Android to AI Engineering DevFeed: [From Android to AI Engineering]() Original publisher: [Read original article]() Author: Lukas Lechner Published: 2026-07-22T15:14:21Z Content type: article Language: en Sources: [Lukas Lechner]() Topics: [AI Engineering](), [Learning](), [software-development]() Tags: [ai](), [ai-engineering](), [allgemein](), [android](), [api](), [applications](), [backend-development](), [boot](), [context](), [costs](), [demand](), [demo](), [frontier-model](), [know](), [llm](), [llms](), [low-latency](), [model](), [story](), [udemy]() ### AI overview The author moved from Android to backend development in 2023, then shifted toward AI Engineering after a client announced it would shut down the service his team supported by the end of 2025. He chose AI Engineering because he saw demand for a newer field with fewer developers already skilled in it, and released an AI Engineering Fundamentals course. He describes AI Engineering as taking LLM applications beyond demos: production work requires finding the least expensive model that still meets needs, optimizing context to control costs, and delivering quick responses. The excerpt begins contrasting demo and production expectations but cuts off before completing that discussion. ### Source excerpt I released a new course "AI Engineering Fundamentals". 👉 https://www.udemy.com/course/ai-engineering-fundamentals-build-real-llm-apps-in-python/?referralCode=D1BA2721D48381A98F83 Below you can find the story about my transition 👇 Many Android Developers know me as the "Coroutines & Flow Guy", since I have the most popular udemy course on that topic. What few people know is that I haven't worked as an Android Developer Read More The post From Android to AI Engineering first appeared on Lukas Lechner. ## Introduction to Backend Development in 2026 DevFeed: [Introduction to Backend Development in 2026]() Original publisher: [Read original article]() Author: snehaa Published: 2026-06-09T07:28:26Z Content type: tutorial Language: en Sources: [Talent500]() Topics: [Back end](), [Database](), [Server](), [software-development](), [App](), [Framework](), [JavaScript](), [Node.js](), [PHP](), [Python](), [Ruby]() Tags: [2026](), [apis](), [applications](), [authentication](), [backend](), [backend-development](), [backend-frameworks](), [databases](), [developer](), [developers](), [development](), [go](), [javascript](), [net](), [newsletters](), [node-js](), [php](), [programming](), [python](), [rest](), [ruby](), [server-side-development](), [technology](), [web-development]() ### AI overview An introductory guide to backend development, explaining how server-side code powers websites and applications through application logic, APIs, databases, authentication, and integrations with other services. ### Source excerpt Backend development sits behind every modern website and application, powering the logic, data, and infrastructure that users never see but [...] The post Introduction to Backend Development in 2026 appeared first on Talent500 blog. ## How to Embed a Checkout Widget in Any Website DevFeed: [How to Embed a Checkout Widget in Any Website]() Original publisher: [Read original article]() Author: Aarthi Poonia Published: 2026-03-30T00:00:00Z Content type: tutorial Language: en Sources: [Dodo Payments Blog]() Topics: [Website](), [WordPress](), [React](), [no-code website builders](), [UI/UX Design]() Tags: [api](), [apple-pay](), [automation](), [backend](), [backend-development](), [billing](), [checkout](), [developer-tools](), [dodo](), [embedding](), [guide](), [how-to](), [html](), [overlay](), [payment](), [payments](), [react](), [website](), [website-builders](), [widget](), [wordpress]() ### AI overview The guide describes three checkout options: an overlay modal that keeps the customer on the current page, an inline form placed in a page container, and a payment link that opens hosted checkout. It gives Dodo Payments SDK setup examples for overlay and inline use, plus CDN-based instructions for plain HTML and WordPress, and embed or code-component approaches for Webflow and Framer. Overlay and inline setups initialize the SDK and open a checkout URL; inline also needs a container and can use a breakdown event for order-summary updates. The guide says a static site can accept payments without a backend using the CDN SDK or payment links, while recommending a backend to create sessions for secure handling and automated fulfillment. It also describes passing customer data, handling return URLs and payment webhooks, and claims card details stay in a provider-served iframe. Tax, customization, and mobile wallet capabilities are presented as Dodo Payments features. ### Source excerpt Guide to embedding a payment checkout widget into any website - HTML, WordPress, React, or website builders. No backend required with Dodo Payments overlay and inline checkout. ## How Bitsets Supercharged Our Backend: Faster String Overlap Checks at Scale DevFeed: [How Bitsets Supercharged Our Backend: Faster String Overlap Checks at Scale]() Original publisher: [Read original article]() Author: Jiaqi Zhu Published: 2026-03-25T19:02:18Z Content type: article Language: en Sources: [Walmart Global Tech]() Topics: [High-Performance Computing](), [Cache](), [database-optimization]() Tags: [access-control](), [approach](), [backend](), [backend-development](), [bottlenecks](), [caching](), [challenge](), [comparisons](), [database](), [deduplication](), [distributed-systems](), [efficiently](), [fast](), [faster](), [fraud](), [hash](), [large](), [lookup](), [loops](), [overlap](), [performance-optimization](), [scale](), [software-engineering](), [string]() ### AI overview The service checks whether request-provided string sets overlap with sets retrieved by key from a backend database, for workflows such as deduplication, access control, and real-time validation. Caching database sets in each pod improved lookup speed but caused memory use to grow unsustainably as the dataset expanded, increasing infrastructure strain and out-of-memory risk. The excerpt says traditional iteration or hash-based comparisons also struggled under heavy load, but ends before describing the bitset design or its measured performance. ### Source excerpt Introduction Ever wondered why your backend slows to a crawl when comparing massive sets of strings? Here's how we turned a bottleneck into a lightning-fast operation using bitsets. Efficiently checking for overlaps between large sets of strings is a common challenge in high-throughput backend services. Traditional approaches -- such as nested loops or hash-based comparisons -- can quickly become performance bottlenecks, especially as data volumes scale and both memory and response time are critical. This is particularly true in environments like Walmart's, where backend systems routinely process millions of records per second to power search, recommendation, and fraud detection features. As our applications grew, we observed that even well-optimized hash set operations struggled to keep up with the demands of real-time processing. In this blog, I'll share how we leveraged bitset optimization to transform our string set overlap checks. The Problem: When "Fast Enough" Isn't Enough Our service is designed to handle high volumes of requests, each containing multiple sets of strings mapped to unique keys -- such as user IDs, product SKUs, or transaction identifiers. For every incoming key, we must efficiently retrieve the corresponding set of strings from our backend database and determine if there is any overlap with the provided set in the request. This overlap check is a critical step in workflows like deduplication, access control, and real-time validation. However, as the number of keys and the size of each string set grow, the computational and memory demands of these operations can escalate rapidly. The Memory Bottleneck To mitigate performance bottlenecks, we initially explored caching the database string sets locally within each pod. While this approach did improve lookup speed, it introduced a new challenge: memory consumption. As our dataset grew, the memory footprint of these in-memory caches ballooned, reaching as high as an unsustainable level in the worst-ca ## Backend Development Engineering in 2026: Skills, Systems and Career Paths DevFeed: [Backend Development Engineering in 2026: Skills, Systems and Career Paths]() Original publisher: [Read original article]() Author: Prachi Kothiyal Published: 2026-01-27T07:08:48Z Content type: article Language: en Sources: [Talent500]() Topics: [Back end](), [software-architecture](), [API](), [Database](), [Microservices](), [Cache](), [Optimization]() Tags: [2026](), [api](), [backend](), [backend-development](), [caching-strategies](), [career-paths-and-learning-routes-for-backend-engineers](), [core-skills-for-backend-engineers-in-2026](), [databases](), [development](), [engineering](), [microservices](), [newsletters](), [optimization](), [trends-redefining-backend-engineering-in-2026](), [what-backend-development-engineering-means-in-2026](), [why-backend-engineering-matters-more-than-ever]() ### AI overview This article explains how backend engineering in 2026 extends beyond server-side coding to include scalable architectures, APIs, service communication, data management, caching, observability, reliability, security, and production-ready engineering skills. It presents backend engineering as an influence on application performance, user experience, search discoverability, and business outcomes. ### Source excerpt What backend development engineering means in 2026 Backend development engineering in 2026 is about far more than writing server-side code. [...] The post Backend Development Engineering in 2026: Skills, Systems and Career Paths appeared first on Talent500 blog. ## Just Launched: Neon Is Now a Kiro Power DevFeed: [Just Launched: Neon Is Now a Kiro Power]() Original publisher: [Read original article]() Author: Carlota Soto Published: 2025-12-03T17:52:39Z Content type: article Language: en Sources: [Neon Docs]() Topics: [Kiro](), [AI Development](), [ide](), [Model Context Protocol](), [Spec Driven Development](), [Back end](), [Deployment]() Tags: [agentic-ai-development](), [ai-development](), [backend-development](), [deployment](), [ide](), [kiro](), [mcp](), [product](), [spec-driven-development]() ### AI overview The article announces Neon as an early launch partner for Kiro powers. It describes a Neon power that lets developers deploy Postgres databases, create production-like branches, run migrations and tests in isolated environments, and revisit past states from within the IDE. It also explains how Kiro powers provide domain-specific tools and knowledge through MCP servers, steering files, and hooks. ### Source excerpt Kiro just announced powers at re:Invent, a new way for developers to access a curated set of tools (each packaged with domain knowledge and best practices) directly from the IDE. Neon is one of the first launch partners, alongside companies like Figma, Stripe, Supabase, Postman,... ## How Understanding Request Flow in Spring Boot Changed the Way I Code DevFeed: [How Understanding Request Flow in Spring Boot Changed the Way I Code]() Original publisher: [Read original article]() Author: Mohammed Published: 2025-12-03T02:02:20Z Content type: article Language: en Sources: [Java Advent Calendar]() Topics: [Spring Boot](), [Back end](), [Code Modularity](), [API]() Tags: [2025](), [annotations](), [api](), [application](), [architecture](), [backend](), [backend-development](), [controllers](), [database](), [di](), [file](), [flow](), [java](), [java-advent](), [jvm](), [layers](), [logic](), [programming](), [project](), [request](), [spring](), [spring-boot](), [springboot](), [structure]() ### AI overview Tracing a Spring Boot API request through the Controller, Service, Repository, and Database helped the author understand why the framework uses layers. The response returns through those layers. The excerpt describes controllers as focused on receiving requests and returning responses, with business logic in the Service and database interactions in the Repository; Spring Data JPA can generate most repository queries. The author says dependency injection reduces tight coupling and inversion of control manages object lifecycles. This personal account presents the flow as a way to make the architecture understandable and the application easier to organize and maintain. ### Source excerpt When I first stepped into backend development, I believed programming was only about one thing: "If the output comes, the job is done." I bundled everything into one giant file -- controllers, logic, database access.I didn't understand why Spring insisted on layers or why DI, IoC, and annotations were so important. The project structure looked [...] The post How Understanding Request Flow in Spring Boot Changed the Way I Code appeared first on JVM Advent. ## We're Hiring a Principal Backend Engineer to Shape the Future of Medium DevFeed: [We're Hiring a Principal Backend Engineer to Shape the Future of Medium]() Original publisher: [Read original article]() Author: Michael Margolis Published: 2025-10-22T17:19:00Z Content type: article Language: en Sources: [Medium]() Topics: [Back end](), [systems](), [Code](), [debugging]() Tags: [architecture](), [backend](), [backend-development](), [engineering](), [hiring](), [medium](), [remote](), [software-engineering](), [us]() ### AI overview Medium is recruiting a Principal Backend Engineer to lead the evolution of its core backend, which supports reading, writing, and discovery. The role includes modernizing the codebase, setting engineering standards, mentoring, and hands-on systems work, and is fully remote in the US. ### Source excerpt When I joined Medium, it was because I still believe in the internet as a place for ideas. Not noise, not outrage, but content that connects people through shared curiosity. Medium's mission is to deepen understanding and spread ideas that matter. We're building the best place for reading and writing online: A space that rewards clarity, authenticity, and craft over clickbait and engagement hacks. That vision only works if the technology beneath it is as thoughtful as the writing above it. That's where you come in. Yes, you! Photo by Yannick Pulver on UnsplashThe Role We are starting the search for a Principal Backend Engineer at Medium, our most senior IC level and a leadership position at the company. In this role, you will lead the evolution of Medium's core backend, the systems that power reading, writing, and discovery for millions of users every day. This is a deeply hands-on, high-impact role. You'll help craft the strategy for where we want to be as an engineering organization on the backend, and be accountable for the quality, standards, and evolution of the Medium backend platform. You will: Partner with engineering, design, data, and executive leadership to define and deliver the future of Medium. Make our platform not just reliable, but genuinely delightful to build on. Modernize a large, living codebase so our teams can move faster and ship with confidence. Lead through influence by setting standards, reviewing critical code and designs, and mentoring engineers across teams. Shape how we build, ensuring our architecture, practices, and systems are strong, scalable, and aligned with Medium's long-term goals. Balance vision with execution by building, debugging, and refining systems yourself to model technical excellence and thoughtful engineering craft. And you can do this work wherever you do your best thinking, whether that's a home office, a beachside Airbnb, a rainy coastal cabin in the Pacific Northwest, or your favorite café with great Wi-Fi and ev ## An Industrial Designer Turned Laravel Dev: The Artisan of the Day Is Morten Harders. DevFeed: [An Industrial Designer Turned Laravel Dev: The Artisan of the Day Is Morten Harders.]() Original publisher: [Read original article]() Author: Ana Tavares Published: 2025-09-05T16:19:21Z Content type: article Language: en Sources: [Laravel Blog]() Topics: [Laravel](), [Back end](), [Developer experience](), [data-architecture](), [phpstorm](), [Developer Tools](), [ide]() Tags: [backend](), [backend-development](), [career](), [community](), [developer-experience](), [laravel](), [phpstorm](), [tooling]() ### AI overview Morten Harders describes his transition from industrial design to professional Laravel development after turning a long-standing coding hobby into a career. He discusses building bespoke applications for different industries, Laravel's role in his work, the Laravel community, and tools such as PhpStorm and Laravel Idea. ### Source excerpt From industrial designer to Laravel developer, Morten Harders shares how a 20-year hobby, encouragement at home, and community shaped his career. ## Why some Go teams use frameworks for structure and consistency DevFeed: [Why some Go teams use frameworks for structure and consistency]() Original publisher: [Read original article]() Author: Marcus Kohlberg Published: 2025-04-30T00:00:00Z Content type: opinion Language: en Sources: [Encore Updates]() Topics: [Go Language](), [Framework](), [Back end](), [Django](), [FastAPI](), [Ruby on Rails]() Tags: [backend-development](), [development](), [django](), [fastapi](), [frameworks](), [go](), [rails]() ### AI overview This opinion article examines the trade-off between Go's simplicity and the lack of centralized conventions for project structure, routing, migrations, and other backend tasks. It argues that teams may benefit from convention-driven frameworks such as Encore, while comparing Go's approach with Rails, Django, and FastAPI. ### Source excerpt Simplicity can be a burden sometimes ## Debugging deadlocks in Postgres DevFeed: [Debugging deadlocks in Postgres]() Original publisher: [Read original article]() Author: Louis Heath Published: 2025-02-04T21:37:00Z Content type: tutorial Language: en Sources: [The incident.io Blog]() Topics: [Deadlock](), [debugging](), [Concurrency](), [Back end](), [Transactions](), [Database]() Tags: [backend-development](), [concurrent](), [database](), [deadlock](), [debugging](), [incident](), [incident-channel](), [incident-management](), [incident-response](), [locks](), [outage](), [post-mortem](), [slack-incident](), [sync](), [transactions]() ### AI overview This article explains how deadlocks arise in Postgres when concurrent processes hold locks that each other needs. It recommends redesigning transactions to acquire locks in a consistent order and discusses alternative approaches that reduce parallelism and may increase lock timeouts. ### Source excerpt Deadlocks are a natural hurdle in backend development, but with a bit of digging and careful design they can be identified and resolved. [Next page]()