Terraform Brings Version Control and Repeatability to AWS Infrastructure

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The article explains infrastructure as code, where cloud resources like servers, databases, networks and permissions are defined in text files stored in Git rather than configured by hand in the AWS console. It argues this approach provides reviewed changes, a clear history, consistent staging and production environments, and the ability to recreate an environment after loss. Terraform is presented as the most widely used tool for this on AWS, valued for its multi-provider support, plan-before-apply workflow, community modules and wide familiarity among DevOps engineers. The piece also covers licensing changes to Terraform, the open-source alternative OpenTofu, and how it compares with AWS's CloudFormation. It recommends a modular project layout with separate state per environment and remote, locked state storage.

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ElevenLabs and Murf.ai Compared for Enterprise Voice AI in 2026

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ProgrammingDEV Community ·

Solo-Developed Megabonk Sells Over One Million Copies in Two Weeks Using Unity

Megabonk, a 3D survivors-style game built by solo developer Vedinad in Unity, launched on Windows and Linux in September 2025. The title reportedly sold over one million copies within two weeks and peaked at 117,336 concurrent players on Steam. The article argues that Unity suited the game's 3D movement, procedurally generated maps, and large volume of characters and items. Compared with Vampire Survivors, which had to be ported to Unity later, Megabonk started on the engine, avoiding a costly rewrite. The developer also withdrew the game from a Game Awards nomination, though the article notes that rough visuals drew some early criticism.

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ProgrammingDEV Community ·

Automating Breach Notifications to Meet Fixed Regulatory Deadlines

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ProgrammingDEV Community ·

Two Sum: Why a Hash Map Turns an O(n²) Interview Problem Into O(n)

Two Sum asks for the indexes of two numbers in a list that add up to a given target, and it is one of the most frequently asked coding interview questions. The obvious brute-force approach checks every pair, which scales quadratically and becomes very slow on large inputs. A faster method reframes the problem: for each number, it checks whether the complement it needs has already been seen, using a dictionary for constant-time lookups. Storing each value only after checking for its complement prevents a number from pairing with itself. The author reports that this single-pass version ran roughly 1,800 times faster than brute force on a test input, and the advantage grows as the list gets longer.

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