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Tutorials, Errors and Exceptions
Its a journey to understand things better. It will have tutorials, any error/exceptions encountered, its resolutions and lots of learning.

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CCA-F Domain 4: Prompt Engineering and Structured Output
As we discussed in the previous post on Domain 3: Claude Code Configuration and Workflow, this part of the post will cover the Domain 4 which holds 20% weightage in the exam. If you have directly stumbled upon this page, I am preparing for the Claude Certified Architect β Foundations (CCA-F), and placing all types of practice questions that I encounter. This may help others, but objective is to keep track of key concept and some practice question that define the topics as wel
Ankit Agrahari
Aug 1911 min read
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CCA-F Domain1: Agentic Architecture & Orchestration - Key Concepts
I am preparing for the Claude Certified Architect β Foundations (CCA-F), and placing all types of practice questions that I encounter. This may help others, but objective is to keep track of key concept and some practice question that define the topics as well. Where to Register: https://anthropic-partners.skilljar.com/claude-certified-architect-foundations-certification Topics Covered agentic vs workflow vs conversational systems, the agentic loop (gather context β act β ver
Ankit Agrahari
Aug 912 min read
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Building DevOps Intelligence using MCP Server with Spring AI: Tools, Challenges & Solutions
Devops Intelligence Today, I successfully built and deployed a Model Context Protocol (MCP) server using Spring AI that exposes real DevOps infrastructure through intelligent tools. But the journey? Let's just say it involved more debugging than coding. In this post, I'll walk you through: What we built (the DevOps Intelligence Platform) The tools we created (K8s, Prometheus, Logs, Deployments) Every challenge we faced (and how we solved them) Why Spring AI 2.0.0-M2 is the s
Ankit Agrahari
Mar 147 min read
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![If this shifted how you think about AI β
you're ready to Harness it. π₯
π¬ Comment "HARNESS" below
β I'll DM you the open-source agent template
π Save this carousel β refer back when you build
π€ Share with one engineer who's still copy-pasting
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![You think HashMap is always O(1).
It isn't. Here's what actually happens. π§΅
HashMap stores pairs using `index = hash(key) % capacity` β direct slot access, no scanning. Pure O(1). Until two keys land on the same slot. That's a collision β not a bug, a math inevitability.
Two ways to fix it π
π Chaining β each bucket holds a linked list. Collisions append to the list. Simple, handles high load, easy deletion. Downside: pointer overhead, poor cache performance, chains degrade to O(n) at high load. Java's fix? At 8 nodes, the list auto-converts to a Red-Black Tree β O(log n) worst case.
π¦ Open Addressing β no linked lists. Collision at slot X? Probe X+1, X+2 until empty. Cache-friendly, zero memory overhead. Downside: deletion needs tombstone markers, and keys cluster together making future collisions worse. Used by C++, Go, Redis.
βοΈ Load Factor = entries Γ· capacity
π’ Below 0.5 β rare collisions, wasted memory
π 0.75 β Java's sweet spot, triggers resize + rehash
π΄ Above 0.9 β collision cascade, O(n) territory
Double hashing kills clustering by varying the probe step per key:
`probe(i) = (h1 + i Γ h2) % m`
Elements scatter evenly. No bunching. O(1) preserved.
The truth: HashMap is O(1) until a bad hash function, wrong load factor, or wrong strategy turns it into O(n).
Three things protect you:
β Well-distributed hash function
β Load factor under 0.75
β Right collision strategy for your use case
π¬ Java interview question: what happens when a chain hits 8 nodes?
Drop your answer below π
π Save this before your next interview.
#java #hashmap #datastructures #dsa #algorithms
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