Raj S retweeted
29 visual guides to build your Cloud, DevOps & AI skills. ๐
Bookmark this list for your next learning session & share ๐
1. Cloud Security Visual Guide
t3pacademy.gumroad.com/l/bhqโฆ
2. Build AI Agents & Workflow Automation
t3pacademy.gumroad.com/l/jqzโฆ
3. DevOps Hiring Checklist
t3pacademy.gumroad.com/l/qypโฆ
4. Cloud Landing Zone Visual Handbook
t3pacademy.gumroad.com/l/tgyโฆ
5. DevOps Roadmap
t3pacademy.gumroad.com/l/vnpโฆ
6. Linux Mastery: 53 Advanced Commands
t3pacademy.gumroad.com/l/nqvโฆ
7. GitHub Actions Visual Guide
t3pacademy.gumroad.com/l/yrmโฆ
8. AWS Containers Mastery
t3pacademy.gumroad.com/l/oreโฆ
9. System Design Visual Guide
t3pacademy.gumroad.com/l/utaโฆ
10. Disaster Recovery Visual Blueprint
t3pacademy.gumroad.com/l/DR-โฆ
11. Terraform Troubleshooting Guide
t3pacademy.gumroad.com/l/Terโฆ
12. AWS Container & Serverless Troubleshooting
t3pacademy.gumroad.com/l/AWSโฆ
13. AWS Cloud Security Cheat Sheet
t3pacademy.gumroad.com/l/awsโฆ
14. AWS + Terraform Deployment Guide
t3pacademy.gumroad.com/l/awsโฆ
15. Linux Interview Handbook
t3pacademy.gumroad.com/l/ogmโฆ
16. AI Engineer Roadmap
t3pacademy.gumroad.com/l/AI-โฆ
17. AI Cheat Sheet for Beginners
t3pacademy.gumroad.com/l/ai-โฆ
18. AI Agent Builderโs Handbook
t3pacademy.gumroad.com/l/mtuโฆ
19. Generative AI Basics
t3pacademy.gumroad.com/l/Genโฆ
20. MLOps for Beginners
t3pacademy.gumroad.com/l/uwjโฆ
21. AI Infrastructure Playbook
t3pacademy.gumroad.com/l/xshโฆ
22. Docker 8-Days Visual Guide
t3pacademy.gumroad.com/l/docโฆ
23. Kubernetes Production Readiness: 100 Checks Before You Go Live
t3pacademy.gumroad.com/l/yqoโฆ
24. From Cloud & DevOps to AI Engineer: The Career Transition Visual Playbook
t3pacademy.gumroad.com/l/Cloโฆ
25. LLM Inference: A Quick Visual Guide
t3pacademy.gumroad.com/l/LLMโฆ
26. 12-Day Docker Mastery: Beginner to Production Visual Guide
t3pacademy.gumroad.com/l/ghwโฆ
27. AI Observability & Evaluation Visual Playbook
t3pacademy.gumroad.com/l/AI-โฆ
28. MCP + A2A Visual Playbook
t3pacademy.gumroad.com/l/MCPโฆ
29. DevOps CI/CD Mastery: 10 Steps to Build a Production-Ready Pipeline
t3pacademy.gumroad.com/l/CI-โฆ
Pick one guide. Learn a concept. Put it into practice.
All guides: t3pacademy.gumroad.com/
~Tech Fusionist
Raj S retweeted
29 FREE Tech Visual Guides (cloud, devops, AI & cybersecurity)
๐ค Made with AI
29 visual guides to build your Cloud, DevOps & AI skills. ๐
Bookmark this list for your next learning session & share ๐
1. Cloud Security Visual Guide
t3pacademy.gumroad.com/l/bhqโฆ
2. Build AI Agents & Workflow Automation
t3pacademy.gumroad.com/l/jqzโฆ
3. DevOps Hiring Checklist
t3pacademy.gumroad.com/l/qypโฆ
4. Cloud Landing Zone Visual Handbook
t3pacademy.gumroad.com/l/tgyโฆ
5. DevOps Roadmap
t3pacademy.gumroad.com/l/vnpโฆ
6. Linux Mastery: 53 Advanced Commands
t3pacademy.gumroad.com/l/nqvโฆ
7. GitHub Actions Visual Guide
t3pacademy.gumroad.com/l/yrmโฆ
8. AWS Containers Mastery
t3pacademy.gumroad.com/l/oreโฆ
9. System Design Visual Guide
t3pacademy.gumroad.com/l/utaโฆ
10. Disaster Recovery Visual Blueprint
t3pacademy.gumroad.com/l/DR-โฆ
11. Terraform Troubleshooting Guide
t3pacademy.gumroad.com/l/Terโฆ
12. AWS Container & Serverless Troubleshooting
t3pacademy.gumroad.com/l/AWSโฆ
13. AWS Cloud Security Cheat Sheet
t3pacademy.gumroad.com/l/awsโฆ
14. AWS + Terraform Deployment Guide
t3pacademy.gumroad.com/l/awsโฆ
15. Linux Interview Handbook
t3pacademy.gumroad.com/l/ogmโฆ
16. AI Engineer Roadmap
t3pacademy.gumroad.com/l/AI-โฆ
17. AI Cheat Sheet for Beginners
t3pacademy.gumroad.com/l/ai-โฆ
18. AI Agent Builderโs Handbook
t3pacademy.gumroad.com/l/mtuโฆ
19. Generative AI Basics
t3pacademy.gumroad.com/l/Genโฆ
20. MLOps for Beginners
t3pacademy.gumroad.com/l/uwjโฆ
21. AI Infrastructure Playbook
t3pacademy.gumroad.com/l/xshโฆ
22. Docker 8-Days Visual Guide
t3pacademy.gumroad.com/l/docโฆ
23. Kubernetes Production Readiness: 100 Checks Before You Go Live
t3pacademy.gumroad.com/l/yqoโฆ
24. From Cloud & DevOps to AI Engineer: The Career Transition Visual Playbook
t3pacademy.gumroad.com/l/Cloโฆ
25. LLM Inference: A Quick Visual Guide
t3pacademy.gumroad.com/l/LLMโฆ
26. 12-Day Docker Mastery: Beginner to Production Visual Guide
t3pacademy.gumroad.com/l/ghwโฆ
27. AI Observability & Evaluation Visual Playbook
t3pacademy.gumroad.com/l/AI-โฆ
28. MCP + A2A Visual Playbook
t3pacademy.gumroad.com/l/MCPโฆ
29. DevOps CI/CD Mastery: 10 Steps to Build a Production-Ready Pipeline
t3pacademy.gumroad.com/l/CI-โฆ
Pick one guide. Learn a concept. Put it into practice.
All guides: t3pacademy.gumroad.com/
~Tech Fusionist
Raj S retweeted
Interviewed a Senior Backend Engineer today.
Knew queues, Redis, databases โ all of it.
Then I asked:
Users can set a reminder for any time in the future.
10 million reminders are pending.
Each must fire within a second of its time.
The engineer said: use setTimeout.
Server restarts.
10 million timers vanish.
Next idea: a cron job every minute
that scans the reminders table.
Full scan of 10 million rows, every minute.
Silence.
How would you design it? ๐
Cisco OSPF Configuration!!! | CCNA 200-301 | IPCisco.com
๐ฅ Join IPCisco Gold Membership: buff.ly/smwGPGz
๐All You Need to Be a Network Engineer!โจ
โ
Complete Network Courses
โ
Thousands of Practice Questions & Quizes
โ
Ready-to-use Packet Tracer & GNS3 Labs
โ
Complete Cheat Sheet Library
โ
Real World Interview Vaults
โ
Lifetime Content Updates
#network #networkengineer #cisco
Raj S retweeted
How does Hibernate guarantee application-level repeatable reads
vladmihalcea.com/hibernate-aโฆ
Raj S retweeted
A beginnerโs guide to JTA Transaction Type
vladmihalcea.com/jta-transacโฆ
Raj S retweeted
8 Deployment Patterns Engineers Should Know:
These patterns all help ship changes, but what actually happens in each strategy is very different and they work at different layers.
Infrastructure Layer
๐ญ) ๐ฅ๐ผ๐น๐น๐ถ๐ป๐ด: the default for stateless services when two versions can safely overlap. Cheap to run, but rollback is just another slow rollout.
๐ฎ) ๐๐น๐๐ฒ-๐ด๐ฟ๐ฒ๐ฒ๐ป: when you need fast rollback and can afford two environments. A shared database makes it harder than it looks.
๐ฏ) ๐ฆ๐ต๐ฎ๐ฑ๐ผ๐: when you're rewriting a critical path and want to test it against real traffic first. You pay for duplicate load and must isolate side effects.
๐ฐ) ๐๐บ๐บ๐๐๐ฎ๐ฏ๐น๐ฒ ๐ถ๐ป๐ณ๐ฟ๐ฎ๐๐๐ฟ๐๐ฐ๐๐๐ฟ๐ฒ: when config drift keeps causing surprises. Replacing instances with tested images improves consistency, but requires reliable image builds and provisioning.
Release Layer
๐ฑ) ๐๐ฒ๐ฎ๐๐๐ฟ๐ฒ ๐ณ๐น๐ฎ๐ด๐: when you want to decouple code deployment from releasing 100% of your changes to everyone instantly. Every flag is a code path you'll have to clean up.
๐ฒ) ๐๐ฎ๐ป๐ฎ๐ฟ๐: when a change is risky and your metrics catch regressions fast. A small group of real users still hits the bug.
๐ณ) ๐ฃ๐ฟ๐ผ๐ด๐ฟ๐ฒ๐๐๐ถ๐๐ฒ ๐ฑ๐ฒ๐น๐ถ๐๐ฒ๐ฟ๐: when you want to control exposure using real production signals. Rollouts can advance or stop based on metrics, but reliable observability is essential.
๐ด) ๐/๐ ๐๐ฒ๐๐๐ถ๐ป๐ด: when the question is "is this better?", not "is this safe?". Results need enough traffic to mean anything.
But these patterns only protect the changes that actually use them.
Feature flags can power canaries, A/B tests, and progressive rollouts. But deciding which changes need flags, setting rollout rules, and cleaning them up still falls to engineers.
LaunchDarkly's new Release Autopilot uses AI agents to automate that setup.
It classifies changes by risk, adds feature flags when needed, and progressively releases changes while monitoring live production signals against defined guardrails. It also helps clean up flags after release.
๐๐
๐ฝ๐น๐ผ๐ฟ๐ฒ ๐ฅ๐ฒ๐น๐ฒ๐ฎ๐๐ฒ ๐๐๐๐ผ๐ฝ๐ถ๐น๐ผ๐ โ lucode.co/release-autopilot-โฆ
What else would you add?
โโ
โป๏ธ Repost to help others learn deployment patterns.
๐ Thanks to @LaunchDarkly for sponsoring this post.
โ Follow me ( Nikki Siapno ) to improve at system design and AI.
Cisco DHCP Configuration!!! | CCNA 200-301 | IPCisco.com
๐ฅ Join IPCisco Gold Membership: buff.ly/smwGPGz
๐All You Need to Be a Network Engineer!โจ
โ
Complete Network Courses
โ
Thousands of Practice Questions & Quizes
โ
Ready-to-use Packet Tracer & GNS3 Labs
โ
Complete Cheat Sheet Library
โ
Real World Interview Vaults
โ
Lifetime Content Updates
#network #networkengineer #cisco
Raj S retweeted
Case Today :
Marriage of 3 years. No child. Wife suddenly tells husband she wants to live away because she is failing at her job and needs to focus to improve performance
Husband gets to know she's cheating on him and job is just a facade
He installs spycam in his bedroom. Wife & her lover caught in the act !!
She was bringing her boyfriend home in absence of husband.
GADAR !!!
Raj S retweeted
๐ ๐๐ฃ ๐๐ ๐ฅ๐๐ ๐๐ ๐๐ ๐๐ด๐ฒ๐ป๐๐.
๐ ๐๐ฃ is the connection layer. It gives AI systems a standard way to connect to external systems and capabilities. MCP servers expose tools for querying databases, calling APIs, or taking actions, without requiring custom integrations for every client. But it handles connectivity, not retrieval.
That's where ๐ฅ๐๐ comes in. It searches your docs at query time, pulling relevant chunks into the prompt so answers can draw from your data. Keeping it current means updating an index, not retraining the model. In a basic RAG pipeline, the flow is straightforward: retrieve, then answer.
Now with ๐๐ ๐๐ด๐ฒ๐ป๐๐, the model runs in a loop: plan a step, call a tool, read the result, repeat until the goal is met. That handles multi-step tasks, at the cost of more latency, tokens, and failure points.
So the choice comes down to the gap you're closing: access to systems, knowledge from your data, or action over many steps.
But executing a task successfully doesn't necessarily mean it's still the right task.
Priorities shift, budgets change, and teams move between projects. Both humans and AI agents can keep executing work that no longer aligns with the bigger plan.
The problem is that strategy, capacity, spend, and execution data often live in different systems. By the time a quarterly review reveals the gap between plan and reality, time and budget have already been spent.
Catching that drift early means continuously connecting what was planned with the work actually happening, across both human teams and AI agents.
Tempo Loop brings together time, capacity, spend, and execution data in one unified view across human and AI-agent work.
It answers a simple question without chasing status updates: Are we still working on the right things?
When something drifts, Loop identifies the gap, recommends corrective actions with tradeoff context, and orchestrates approved changes back into the systems teams already use, like Jira.
๐๐ด๐ฒ๐ป๐๐ ๐น๐ผ๐ผ๐ฝ ๐ผ๐ป ๐๐ฎ๐๐ธ๐. ๐ง๐ต๐ถ๐ ๐ผ๐ป๐ฒ ๐น๐ผ๐ผ๐ฝ๐ ๐ผ๐ป ๐ฝ๐ฟ๐ถ๐ผ๐ฟ๐ถ๐๐ถ๐ฒ๐.
๐ฆ๐ฒ๐ฒ ๐ต๐ผ๐ ๐ง๐ฒ๐บ๐ฝ๐ผ ๐๐ผ๐ผ๐ฝ ๐๐ผ๐ฟ๐ธ๐ โ lucode.co/tempo-loop-z71xd
What else would you add?
โโ
โป๏ธ Repost to help others learn AI.
๐ Thanks to @TempoHQ for sponsoring this post.
โ Follow me ( Nikki Siapno ) to improve at AI and system design.
Routing Protocols!!! | CCNA 200-301 | IPCisco.com
๐ฅ Join IPCisco Gold Membership: buff.ly/smwGPGz
๐All You Need to Be a Network Engineer!โจ
โ
Complete Network Courses
โ
Thousands of Practice Questions & Quizes
โ
Ready-to-use Packet Tracer & GNS3 Labs
โ
Complete Cheat Sheet Library
โ
Real World Interview Vaults
โ
Lifetime Content Updates
#network #networkengineer #cisco
HLD Interview Notes: Day 17/30
Topic: CDN: Content Delivery Networks and Edge Caching
Imagine millions of users accessing images, videos, CSS, and JavaScript files.
If every request reaches your origin server, latency increases and the server can become overloaded.
How do we deliver content faster?
That's where a CDN comes in.
What Is a CDN?
A Content Delivery Network (CDN) is a geographically distributed network of servers that delivers content from locations closer to users.
It helps improve:
โข Content delivery speed
โข Global application performance
โข Availability
โข Origin server scalability
โข Bandwidth efficiency
How Does a CDN Work?
Without a CDN:
User โ Origin Server โ User
Every request travels to the origin server, even when users are geographically far away.
With a CDN:
User โ Nearby CDN Edge โ User
The CDN checks whether the requested content is cached.
โข Cache Hit: Returns content directly from the edge server.
โข Cache Miss: Fetches content from the origin server and may cache it for future requests.
What Is Edge Caching?
Edge caching stores frequently requested content on CDN servers closer to users.
Example:
An e-commerce website serves the same product image to thousands of users.
Instead of repeatedly fetching it from the origin server, the CDN stores a copy at an edge location.
Benefits:
โข Lower latency
โข Reduced origin traffic
โข Faster content delivery
โข Better handling of traffic spikes
What Is Cache TTL?
TTL stands for Time To Live.
It determines how long cached content remains valid before it needs to be refreshed or revalidated.
Example:
A product image is cached for 24 hours.
After the TTL expires, the CDN can fetch a fresh version or revalidate the existing copy.
Common techniques:
โข Cache-Control headers
โข ETag validation
โข Versioned URLs
โข Cache invalidation
What Is Cache Invalidation?
Cache invalidation removes or marks cached content as stale when the original content changes.
Example:
A seller updates a product image, but the CDN still stores the old version.
Common solutions:
โข Cache Purging: Remove cached content.
โข Versioned URLs: Use a new URL for updated content.
โข TTL Expiration: Let cached content expire.
โข Revalidation: Check content freshness using ETags.
CDN vs Origin Server
Origin Server:
Stores the original content and handles requests when the CDN cannot serve a valid cached response.
CDN Edge Server:
Stores cached copies closer to users and handles repeated requests.
Remember: The origin is the source of truth. The CDN improves content delivery.
What Content Should Be Cached?
Static Content:
โข Images
โข CSS and JavaScript
โข Fonts
โข Videos
โข Documents
Dynamic Content:
Personalized data, account information, and frequently changing responses require careful caching rules.
Incorrect caching can expose private data or serve outdated information.
Where Is It Used?
โข E-commerce platforms
โข Video streaming applications
โข Social media platforms
โข Gaming platforms
โข News websites
โข Software download platforms
Popular providers: Cloudflare, Amazon CloudFront, and Akamai.
Common Interview Mistakes
โข Confusing CDN with a load balancer.
โข Assuming every request is a cache hit.
โข Ignoring cache invalidation.
โข Choosing an inappropriate TTL.
โข Caching sensitive data incorrectly.
โข Forgetting origin fallback.
โข Assuming a CDN automatically improves database performance.
Interview Questions
What is a CDN?
How does a CDN reduce latency?
What is an edge server?
Cache Hit vs Cache Miss?
What is Edge Caching?
What is TTL?
How does cache invalidation work?
CDN vs Load Balancer?
How are cache misses handled?
How would you design a global image delivery system?
FAANG Takeaway
A CDN improves application performance by distributing cached content across geographically distributed edge servers.
The key decisions are:
โข What should be cached?
โข How long should it be cached?
โข How should stale content be refreshed?
Remember:
CDN brings content closer to users. Edge caching reduces repeated requests to the origin server.
Next: Day 18/30
Rate Limiting: Controlling Traffic in Distributed Systems
Raj S retweeted
Cybersecurity Learning Plan (6 weeks, 42 days)
Cybersecurity in 6 Weeks: Zero to Practical Skills ๐
Week 1: Networking & Linux Fundamentals
Day 1: TCP/IP, OSI Model
Day 2: DNS, HTTP/HTTPS, SSH
Day 3: IP Addressing, Subnets, Ports
Day 4: Linux Commands & Permissions
Day 5: Firewalls, VPNs & Protocols
Day 6: Wireshark & Packet Analysis
Day 7: Hands-on Networking Lab
Week 2: Cybersecurity Fundamentals
Day 8: CIA Triad & Security Principles
Day 9: Common Cyberattacks & Threats
Day 10: Encryption, Hashing & PKI
Day 11: Authentication, MFA & IAM
Day 12: Vulnerabilities, CVEs & CVSS
Day 13: OWASP Top 10
Day 14: Security Assessment Lab
Week 3: Ethical Hacking & Penetration Testing
Day 15: Ethical Hacking Methodology
Day 16: Nmap & Network Scanning
Day 17: Vulnerability Assessment
Day 18: Burp Suite & Web Security
Day 19: SQL Injection & XSS Basics
Day 20: Metasploit Fundamentals
Day 21: Practice on Legal CTF Labs
Week 4: SOC & Defensive Security
Day 22: SOC Operations & Blue Team
Day 23: SIEM & Log Analysis
Day 24: Splunk / Wazuh Basics
Day 25: IDS, IPS & EDR
Day 26: MITRE ATT&CK Framework
Day 27: Threat Hunting & Detection
Day 28: Build a Mini SOC Lab
Week 5: Cloud Security & DevSecOps
Day 29: AWS / Azure Security Basics
Day 30: Cloud IAM & Least Privilege
Day 31: Cloud Logging & Monitoring
Day 32: Container & Kubernetes Security
Day 33: SAST, DAST & Dependency Scanning
Day 34: Secrets Management & Zero Trust
Day 35: Secure a Cloud Application
Week 6: Incident Response & Real Projects
Day 36: Incident Response Lifecycle
Day 37: Digital Forensics Fundamentals
Day 38: Malware Analysis Basics
Day 39: Security Automation with Python
Day 40: AI Security & Prompt Injection
Day 41: Cybersecurity Interview Scenarios
Day 42: Final Project + GitHub Portfolio
42 Days. 6 Weeks. 6 Practical Labs.
Don't just memorize security tools. Learn how attacks work, how to detect them, and how to defend real systems.
Save this roadmap and start building your cybersecurity skills. ๐
Raj S retweeted
Senior backend interview question:
A Node.js service gets OOM-killed
every 9 hours.
Heap snapshots look normal.
Never reproduces locally.
No obvious leak in the code.
What are you checking first?
Raj S retweeted
Cybersecurity Learning Plan (6 Weeks, 42 days)
Cybersecurity in 6 Weeks: Zero to Practical Skills ๐
Week 1: Networking & Linux Fundamentals
Day 1: TCP/IP, OSI Model
Day 2: DNS, HTTP/HTTPS, SSH
Day 3: IP Addressing, Subnets, Ports
Day 4: Linux Commands & Permissions
Day 5: Firewalls, VPNs & Protocols
Day 6: Wireshark & Packet Analysis
Day 7: Hands-on Networking Lab
Week 2: Cybersecurity Fundamentals
Day 8: CIA Triad & Security Principles
Day 9: Common Cyberattacks & Threats
Day 10: Encryption, Hashing & PKI
Day 11: Authentication, MFA & IAM
Day 12: Vulnerabilities, CVEs & CVSS
Day 13: OWASP Top 10
Day 14: Security Assessment Lab
Week 3: Ethical Hacking & Penetration Testing
Day 15: Ethical Hacking Methodology
Day 16: Nmap & Network Scanning
Day 17: Vulnerability Assessment
Day 18: Burp Suite & Web Security
Day 19: SQL Injection & XSS Basics
Day 20: Metasploit Fundamentals
Day 21: Practice on Legal CTF Labs
Week 4: SOC & Defensive Security
Day 22: SOC Operations & Blue Team
Day 23: SIEM & Log Analysis
Day 24: Splunk / Wazuh Basics
Day 25: IDS, IPS & EDR
Day 26: MITRE ATT&CK Framework
Day 27: Threat Hunting & Detection
Day 28: Build a Mini SOC Lab
Week 5: Cloud Security & DevSecOps
Day 29: AWS / Azure Security Basics
Day 30: Cloud IAM & Least Privilege
Day 31: Cloud Logging & Monitoring
Day 32: Container & Kubernetes Security
Day 33: SAST, DAST & Dependency Scanning
Day 34: Secrets Management & Zero Trust
Day 35: Secure a Cloud Application
Week 6: Incident Response & Real Projects
Day 36: Incident Response Lifecycle
Day 37: Digital Forensics Fundamentals
Day 38: Malware Analysis Basics
Day 39: Security Automation with Python
Day 40: AI Security & Prompt Injection
Day 41: Cybersecurity Interview Scenarios
Day 42: Final Project + GitHub Portfolio
42 Days. 6 Weeks. 6 Practical Labs.
Don't just memorize security tools. Learn how attacks work, how to detect them, and how to defend real systems.
Save this roadmap and start building your cybersecurity skills. ๐
Raj S retweeted
Cybersecurity in 6 Weeks: Zero to Practical Skills ๐
Week 1: Networking & Linux Fundamentals
Day 1: TCP/IP, OSI Model
Day 2: DNS, HTTP/HTTPS, SSH
Day 3: IP Addressing, Subnets, Ports
Day 4: Linux Commands & Permissions
Day 5: Firewalls, VPNs & Protocols
Day 6: Wireshark & Packet Analysis
Day 7: Hands-on Networking Lab
Week 2: Cybersecurity Fundamentals
Day 8: CIA Triad & Security Principles
Day 9: Common Cyberattacks & Threats
Day 10: Encryption, Hashing & PKI
Day 11: Authentication, MFA & IAM
Day 12: Vulnerabilities, CVEs & CVSS
Day 13: OWASP Top 10
Day 14: Security Assessment Lab
Week 3: Ethical Hacking & Penetration Testing
Day 15: Ethical Hacking Methodology
Day 16: Nmap & Network Scanning
Day 17: Vulnerability Assessment
Day 18: Burp Suite & Web Security
Day 19: SQL Injection & XSS Basics
Day 20: Metasploit Fundamentals
Day 21: Practice on Legal CTF Labs
Week 4: SOC & Defensive Security
Day 22: SOC Operations & Blue Team
Day 23: SIEM & Log Analysis
Day 24: Splunk / Wazuh Basics
Day 25: IDS, IPS & EDR
Day 26: MITRE ATT&CK Framework
Day 27: Threat Hunting & Detection
Day 28: Build a Mini SOC Lab
Week 5: Cloud Security & DevSecOps
Day 29: AWS / Azure Security Basics
Day 30: Cloud IAM & Least Privilege
Day 31: Cloud Logging & Monitoring
Day 32: Container & Kubernetes Security
Day 33: SAST, DAST & Dependency Scanning
Day 34: Secrets Management & Zero Trust
Day 35: Secure a Cloud Application
Week 6: Incident Response & Real Projects
Day 36: Incident Response Lifecycle
Day 37: Digital Forensics Fundamentals
Day 38: Malware Analysis Basics
Day 39: Security Automation with Python
Day 40: AI Security & Prompt Injection
Day 41: Cybersecurity Interview Scenarios
Day 42: Final Project + GitHub Portfolio
42 Days. 6 Weeks. 6 Practical Labs.
Don't just memorize security tools. Learn how attacks work, how to detect them, and how to defend real systems.
Save this roadmap and start building your cybersecurity skills. ๐
Raj S retweeted
How an AI Agent works (visually explained).
3 important shifts coming to customer experience, as @maltekosub put it:
โ Personal AI agents will drive explosive volumes.
โ AI in CX becomes a revenue driver.
โ AI agents evolve into self-improving systems.
The third is the one I'm watching most.
An agent that learns from its own conversations needs strong evaluation and observability, or it can get worse with confidence. Parloa is bringing this to its first customers in the next few months.

























