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Redis Training — Topic-Wise Mock Tests
Choose any syllabus topic below to start a live timed MCQ exam (max 2 attempts per topic per day). Want structured live classes with a seasoned Industry Expert, all 244 full-length Mock Test sets, real module projects, Live Client Production deployment & Official Internship Letter? Enroll in the complete cohort for just ₹2,999!
All Modules & Topics in Redis Training
Redis Architecture — Single-Threaded `epoll` Event Loop, I/O Threads, RESP3 & Sub-Millisecond RAM Speed
Purpose: To understand and apply Redis Architecture — Single-Threaded `epoll` Event Loop, I/O Threads, RESP3 & Sub-Millisecond RAM Speed in real Redis systems — specifically: Why **REmote DIctionary Server** achieves `<0.5 ms` p99 latency and `100k+ ops/sec` on a single core: zero mutex lock contention on the main command-execution thread, kernel `epoll`/`kqueue` non-blocking socket multiplexing, Redis 6/7 threaded network socket read/write (`io-threads`), and binary-safe `RESP2`/`RESP3` wire framing, so your code stays reliable, fast, and easy to maintain in production.
Redis vs RDBMS — Polyglot Persistence, Cache-Aside vs Write-Through & Stampede / Avalanche Defense
Purpose: To understand and apply Redis vs RDBMS — Polyglot Persistence, Cache-Aside vs Write-Through & Stampede / Avalanche Defense in real Redis systems — specifically: Why Redis complements (rather than blindly replaces) PostgreSQL/MySQL: ACID system-of-record disk durability + ad-hoc SQL joins in RDBMS vs ephemeral/semi-persistent `O(1)` hot reads, counters, leaderboards, and locks in Redis; plus Cache-Aside (` Read: Cache -> DB -> Set Cache; Write: Update DB -> Delete Cache!`) and TTL jitter, so your code stays reliable, fast, and easy to maintain in production.
Installing Redis 7 in Production — `vm.overcommit_memory=1`, Disabling `THP` & `systemd` Supervision
Purpose: To understand and apply Installing Redis 7 in Production — `vm.overcommit_memory=1`, Disabling `THP` & `systemd` Supervision in real Redis systems — specifically: Installing official `packages.redis.io` / Alpine OCI images (`redis:7.4-alpine`), `supervised systemd`, and why Redis logs startup warnings if Linux `vm.overcommit_memory` is `0` (`fork()` fails with `Cannot allocate memory` even when 40% RAM is free!) or Transparent Huge Pages (`THP`) are enabled!, so your code stays reliable, fast, and easy to maintain in production.
Redis Configuration (`redis.conf`) — `maxmemory-policy` (`LFU` vs `LRU`), `lazyfree` & `CONFIG REWRITE`
Purpose: To understand and apply Redis Configuration (`redis.conf`) — `maxmemory-policy` (`LFU` vs `LRU`), `lazyfree` & `CONFIG REWRITE` in real Redis systems — specifically: Navigating `redis.conf`: network `bind 127.0.0.1 -::1` & `protected-mode yes`, `tcp-keepalive 300`, `maxmemory` & the 8 `maxmemory-policy` modes (`noeviction`, `allkeys-lru`, `allkeys-lfu`, `volatile-lru`, `volatile-lfu`, `volatile-ttl`), `lazyfree-lazy-eviction yes` non-blocking background thread eviction, and live `CONFIG SET` + `CONFIG REWRITE`, so your code stays reliable, fast, and easy to maintain in production.
Redis Data Types Overview — Core 5 + `HyperLogLog` (`12 KB`), Bitmaps, Geospatial & Streams
Purpose: To understand and apply Redis Data Types Overview — Core 5 + `HyperLogLog` (`12 KB`), Bitmaps, Geospatial & Streams in real Redis systems — specifically: Choosing the right data structure: Strings (`SDS` binary-safe <=`512 MB`), Hashes (field-value objects), Lists (`quicklist` queues), Sets (unique membership/intersections), Sorted Sets (`skiplist` leaderboards), **Bitmaps** (`1 bit` per user daily active flag!), **HyperLogLog** (`PFADD`/`PFCOUNT` counting billions of unique items in **`12 KB`**!), **Geo** (`GEOADD`/`GEOSEARCH`), and **Streams** (`XADD`/`XREADGROUP`), so your code stays reliable, fast, and easy to maintain in production.
Redis Key Management — Colon Namespaces, Cursor `SCAN` (Never `KEYS *`!), `UNLINK` vs `DEL` & `TTL`
Purpose: To understand and apply Redis Key Management — Colon Namespaces, Cursor `SCAN` (Never `KEYS *`!), `UNLINK` vs `DEL` & `TTL` in real Redis systems — specifically: Designing clean `app:domain:id` key schemas, inspecting existence & expiry (`EXISTS`, `TTL` returning `-2` missing / `-1` no expiry / `>=0` seconds, `PTTL`, `EXPIRE`, `PERSIST`), why `KEYS *` causes production outages (`O(N)` full-keyspace stop-the-world scan), `SCAN cursor MATCH pattern COUNT 500`, and `UNLINK` background thread reclamation, so your code stays reliable, fast, and easy to maintain in production.
Redis Strings (`SDS`) — `SET NX PX` Atomic Locks, `INCRBY` Counters, `MGET` & `GETDEL`
Purpose: To understand and apply Redis Strings (`SDS`) — `SET NX PX` Atomic Locks, `INCRBY` Counters, `MGET` & `GETDEL` in real Redis systems — specifically: Why Redis uses C **Simple Dynamic Strings (`SDS`)** instead of null-terminated `char*` (`O(1)` `STRLEN`, binary safety for MessagePack/Protobuf bytes up to `512 MB`, buffer-overflow immunity), atomic `SET key token NX PX 5000` locks/idempotency keys, `GETEX`/`GETDEL` one-time OTP verification, and `INCR`/`INCRBY`, so your code stays reliable, fast, and easy to maintain in production.
Redis Hashes — Compact `listpack` Object Modeling, `HSET` / `HMGET` / `HINCRBY` & Avoiding `HGETALL` Stalls
Purpose: To understand and apply Redis Hashes — Compact `listpack` Object Modeling, `HSET` / `HMGET` / `HINCRBY` & Avoiding `HGETALL` Stalls in real Redis systems — specifically: Storing structured entities (`user:1001 -> {name, plan, credits}`) inside a single Redis Hash instead of 8 separate String keys (slashing `dictEntry` pointer overhead by `5x–8x`!), atomic field mutations (`HINCRBY user:1001 credits -1` without JSON deserialize-modify-serialize races!), and `HMGET` vs `HSCAN`, so your code stays reliable, fast, and easy to maintain in production.
Redis Lists (`quicklist`) — `LPUSH`/`RPOP`, Capped `LTRIM` Feeds & Crash-Safe `BLMOVE` Queues
Purpose: To understand and apply Redis Lists (`quicklist`) — `LPUSH`/`RPOP`, Capped `LTRIM` Feeds & Crash-Safe `BLMOVE` Queues in real Redis systems — specifically: How Redis implements Lists as a **`quicklist`** (a doubly-linked list of compact `listpack` chunks — giving `O(1)` head/tail push-pop WITHOUT per-element `prev/next` pointer bloat!), `BLPOP` blocking waits (`0` CPU busy-polling!), why plain `BRPOP` loses the message if the worker dies mid-task, and atomic `BLMOVE` reliable queues, so your code stays reliable, fast, and easy to maintain in production.
Redis Sets — `O(1)` `SISMEMBER`, `SMISMEMBER` Batch Checks, `intset` Encoding & Set Algebra (`SINTER`)
Purpose: To understand and apply Redis Sets — `O(1)` `SISMEMBER`, `SMISMEMBER` Batch Checks, `intset` Encoding & Set Algebra (`SINTER`) in real Redis systems — specifically: Unordered collections of unique strings: `O(1)` membership (`SISMEMBER`) and Redis 6.2+ batch `SMISMEMBER` (checking 50 liked post IDs in 1 command!), `SPOP` (random removal, e.g. raffle/prize pool) vs `SRANDMEMBER` (non-destructive sample), `SINTER` / `SUNION` / `SDIFF`, and compact sorted **`intset`** encoding for integer Sets (`<=512` ints), so your code stays reliable, fast, and easy to maintain in production.
Redis Sorted Sets (`ZSET`) — Dual `Dict + SkipList` Internals, Leaderboards & Sliding-Window Rate Limiting
Purpose: To understand and apply Redis Sorted Sets (`ZSET`) — Dual `Dict + SkipList` Internals, Leaderboards & Sliding-Window Rate Limiting in real Redis systems — specifically: Redis’s crown-jewel structure: every large `ZSET` maintains BOTH a **Hash Table** (`member -> score` in `O(1)`) AND a probabilistic multi-level **SkipList** (sorted by `IEEE-754 double score`, breaking score ties lexicographically by member bytes in `O(log N)`!), powering live leaderboards, priority delay queues (`ZMPOP`), and sliding-window rate limiters, so your code stays reliable, fast, and easy to maintain in production.
Redis `HSET` & Hash Expiration — Key-Level `EXPIRE` vs Redis 7.4 Native Per-Field `HEXPIRE` & `HTTL`
Purpose: To understand and apply Redis `HSET` & Hash Expiration — Key-Level `EXPIRE` vs Redis 7.4 Native Per-Field `HEXPIRE` & `HTTL` in real Redis systems — specifically: Solving a decade-long Redis interview classic! Prior to Redis 7.4, `EXPIRE` worked ONLY on top-level keys (not individual Hash fields) — AND note that `HSET` preserves existing key TTL (unlike `SET` without `KEEPTTL`, which wipes TTL!). In **Redis 7.4+**, native Hash Field Expiration (`HEXPIRE`, `HPEXPIRE`, `HEXPIREAT`, `HTTL`, `HPERSIST`) expires individual fields inside a Hash independently!, so your code stays reliable, fast, and easy to maintain in production.
Redis Transactions — `MULTI` / `EXEC` / `DISCARD`, Why There Is NO Rollback & `WATCH` Optimistic CAS
Purpose: To understand and apply Redis Transactions — `MULTI` / `EXEC` / `DISCARD`, Why There Is NO Rollback & `WATCH` Optimistic CAS in real Redis systems — specifically: How `MULTI` queues commands (`QUEUED`) and `EXEC` runs the entire batch sequentially without interleaving any other client’s commands; the #1 Redis interview gotcha (**Redis does NOT roll back already-executed commands if a later command inside `EXEC` fails at runtime, e.g., `INCR` on a List!**); and Check-And-Set (`CAS`) via `WATCH`, so your code stays reliable, fast, and easy to maintain in production.
Redis Lua Scripting & Functions — Atomic `EVALSHA`, Safe Lock Release & `KEYS[]` vs `ARGV[]` Rule
Purpose: To understand and apply Redis Lua Scripting & Functions — Atomic `EVALSHA`, Safe Lock Release & `KEYS[]` vs `ARGV[]` Rule in real Redis systems — specifically: Why embedded Lua 5.1 (`EVAL`, `EVALSHA`, and Redis 7 persistent `FUNCTION LOAD` / `FCALL`) beats `WATCH/MULTI/EXEC`: zero network round-trips mid-transaction, zero `WatchError` retry storms, true conditional branching (`if/else` on `redis.call` results!), powering Redlock/lock-release and Token-Bucket rate limiters, so your code stays reliable, fast, and easy to maintain in production.
Redis Pipelining — Defeating Network `RTT` Latency, `transaction=False` & Bounded Batch Sizes
Purpose: To understand and apply Redis Pipelining — Defeating Network `RTT` Latency, `transaction=False` & Bounded Batch Sizes in real Redis systems — specifically: Why Redis throughput in microservices is almost always bottlenecked by **network Round-Trip Time (`RTT` ~`0.5 ms`)** + `read()/write()` syscall context switches rather than Redis CPU (`~1 us`!), how Pipelining streams `K` commands in `1` TCP write and reads `K` replies in `1` read (`20x` speedup!), and why Pipelining != Atomic Transaction, so your code stays reliable, fast, and easy to maintain in production.
Redis Connections & Pooling — `ConnectionPool`, Timeouts, `CLIENT LIST` & Async `redis.asyncio`
Purpose: To understand and apply Redis Connections & Pooling — `ConnectionPool`, Timeouts, `CLIENT LIST` & Async `redis.asyncio` in real Redis systems — specifically: Why opening a brand-new TCP + TLS + `AUTH` handshake per HTTP request kills latency and exhausts ephemeral ports (`maxclients` default `10,000`), sharing a thread-safe `redis.ConnectionPool` (or `redis.asyncio` in FastAPI/uvloop), `CLIENT SETNAME` observability in `CLIENT LIST`, RESP3 client-side caching, and socket timeout discipline, so your code stays reliable, fast, and easy to maintain in production.
Redis Backup, Restore & Persistence — `BGSAVE` (`RDB`) vs `AOF` (`everysec`) & Hybrid RDB-Preamble
Purpose: To understand and apply Redis Backup, Restore & Persistence — `BGSAVE` (`RDB`) vs `AOF` (`everysec`) & Hybrid RDB-Preamble in real Redis systems — specifically: Comparing **RDB** (compact point-in-time binary `dump.rdb` created via child `fork()` `BGSAVE` — fast restores & S3 off-site backups, but loses minutes since last snapshot) vs **AOF** (`appendfsync everysec` losing at most `1 second` of writes + `BGREWRITEAOF` compaction), and Redis 7 Multi-Part AOF (`manifest` + `base.rdb` + `incr.aof`), so your code stays reliable, fast, and easy to maintain in production.
Redis 7 Security Hardening — Granular `ACL`s (Key & Command Prefixes), `default off`, TLS 1.3 & VPC Isolation
Purpose: To understand and apply Redis 7 Security Hardening — Granular `ACL`s (Key & Command Prefixes), `default off`, TLS 1.3 & VPC Isolation in real Redis systems — specifically: Why exposed unauthenticated `0.0.0.0:6379` Redis instances get cryptomined within minutes (`CONFIG SET dir /root/.ssh` exploit!): network `bind` + `protected-mode yes` + private VPC Security Groups, disabling `user default off`, creating per-service **Redis 6/7 ACLs** (`~prefix:*`, `&channel:*`, `+@read +@write -@dangerous -@admin`), and mTLS encryption in transit, so your code stays reliable, fast, and easy to maintain in production.
Redis Benchmarking & Latency Forensics — `redis-benchmark` (`-r`, `-d`, `-P`), `--intrinsic-latency` & Tail p99
Purpose: To understand and apply Redis Benchmarking & Latency Forensics — `redis-benchmark` (`-r`, `-d`, `-P`), `--intrinsic-latency` & Tail p99 in real Redis systems — specifically: Running honest load tests with `redis-benchmark`: why omitting `-r <keyspacelen>` hammers the **same 1 single key** in L1 CPU cache, testing realistic payload bytes (`-d 512`), measuring pipeline scaling (`-P 16`), multi-threaded client generation (`--threads 4` from a **separate** VM so benchmark client CPU doesn’t starve `redis-server`!), and `redis-cli --latency-history`, so your code stays reliable, fast, and easy to maintain in production.
Redis Partitioning & Cluster HA — Sentinel vs `16,384` Hash Slots (`CRC16`), `{HashTags}` & `CROSSSLOT`
Purpose: To understand and apply Redis Partitioning & Cluster HA — Sentinel vs `16,384` Hash Slots (`CRC16`), `{HashTags}` & `CROSSSLOT` in real Redis systems — specifically: Scaling Redis horizontally: why naive `hash(key) % N` loses `(N-1)/N` of keys when adding a node vs Consistent Hashing vs **Redis Cluster’s `16,384` deterministic Hash Slots** (`slot = CRC16(key) & 16383`), minimum **6-node production topology** (`3 Primaries + 3 Replicas`), smart client `MOVED`/`ASK` slot maps (`RedisCluster`), and `{user:42}` **Hash Tags** for multi-key operations, so your code stays reliable, fast, and easy to maintain in production.
Cache-Aside, Read/Write-Through, Negative Caching & TTL Jitter
Purpose: To understand and apply Cache-Aside, Read/Write-Through, Negative Caching & TTL Jitter in real Redis systems — specifically: Protect SQL/NoSQL databases from both hot-key floods and repeated missing-ID lookups, so your code stays reliable, fast, and easy to maintain in production.
Preventing Cache Stampedes (Thundering Herd) with Single-Flight Locks & XFetch
Purpose: To understand and apply Preventing Cache Stampedes (Thundering Herd) with Single-Flight Locks & XFetch in real Redis systems — specifically: Recompute expiring popular keys on 1 worker while 5,000 readers still get instant responses, so your code stays reliable, fast, and easy to maintain in production.
Command Pipelining, Connection Pooling & Avoiding O(N) KEYS/SMEMBERS
Purpose: To understand and apply Command Pipelining, Connection Pooling & Avoiding O(N) KEYS/SMEMBERS in real Redis systems — specifically: Slash network round-trip latency 10x and use cursor SCAN so Redis’s single thread never stalls, so your code stays reliable, fast, and easy to maintain in production.
Compact Encodings (ziplist/listpack), maxmemory-policy Eviction & MEMORY USAGE
Purpose: To understand and apply Compact Encodings (ziplist/listpack), maxmemory-policy Eviction & MEMORY USAGE in real Redis systems — specifically: Cut Redis RAM bills by 50% and choose allkeys-lfu vs volatile-lru intentionally, so your code stays reliable, fast, and easy to maintain in production.
Server-Side Atomic EVALSHA Lua Scripts vs Optimistic WATCH/MULTI
Purpose: To understand and apply Server-Side Atomic EVALSHA Lua Scripts vs Optimistic WATCH/MULTI in real Redis systems — specifically: Execute multi-step check-and-decrement logic atomically in microseconds with zero race windows, so your code stays reliable, fast, and easy to maintain in production.
Token-Bucket & ZSET Sliding-Window Rate Limiters
Purpose: To understand and apply Token-Bucket & ZSET Sliding-Window Rate Limiters in real Redis systems — specifically: Enforce exact per-user, per-IP, and per-API-key request quotas across 20 API servers, so your code stays reliable, fast, and easy to maintain in production.
Safe Distributed Mutexes (SET key token NX PX + Lua Safe-Unlock)
Purpose: To understand and apply Safe Distributed Mutexes (SET key token NX PX + Lua Safe-Unlock) in real Redis systems — specifically: Guarantee an expired worker never accidentally deletes a lock acquired by a newer worker!, so your code stays reliable, fast, and easy to maintain in production.
Probabilistic Structures: HyperLogLog Unique Counts & Geo/Leaderboard ZSETs
Purpose: To understand and apply Probabilistic Structures: HyperLogLog Unique Counts & Geo/Leaderboard ZSETs in real Redis systems — specifically: Count 100M unique daily visitors in just 12 KB of RAM and rank live leaderboards in O(log N), so your code stays reliable, fast, and easy to maintain in production.
Pub/Sub Fire-and-Forget Fanout vs Persistent Redis Streams (XADD/XREADGROUP)
Purpose: To understand and apply Pub/Sub Fire-and-Forget Fanout vs Persistent Redis Streams (XADD/XREADGROUP) in real Redis systems — specifically: Know when ephemeral WebSocket broadcast fits vs durable consumer-group event logs, so your code stays reliable, fast, and easy to maintain in production.
Consumer Group Acknowledgments (XACK), Pending Entries (XPENDING) & XAUTOCLAIM
Purpose: To understand and apply Consumer Group Acknowledgments (XACK), Pending Entries (XPENDING) & XAUTOCLAIM in real Redis systems — specifically: Reassign unacknowledged messages automatically when a worker container crashes mid-job, so your code stays reliable, fast, and easy to maintain in production.
Stream Trimming (MAXLEN ~), Idempotent Deduplication & Dead-Letter Streams
Purpose: To understand and apply Stream Trimming (MAXLEN ~), Idempotent Deduplication & Dead-Letter Streams in real Redis systems — specifically: Bound stream memory predictably and quarantine poison messages cleanly, so your code stays reliable, fast, and easy to maintain in production.
Delayed Job Schedulers Using ZSET Timestamps + Atomic Lua Promotion
Purpose: To understand and apply Delayed Job Schedulers Using ZSET Timestamps + Atomic Lua Promotion in real Redis systems — specifically: Build rock-solid scheduled reminders and retry queues on pure Redis primitives, so your code stays reliable, fast, and easy to maintain in production.
RDB Snapshots vs Append-Only File (appendfsync everysec) Hybrid Persistence
Purpose: To understand and apply RDB Snapshots vs Append-Only File (appendfsync everysec) Hybrid Persistence in real Redis systems — specifically: Balance sub-millisecond write speed with at-most-1-second crash durability, so your code stays reliable, fast, and easy to maintain in production.
Redis Sentinel Quorum Monitoring & Client-Aware Automatic Failover
Purpose: To understand and apply Redis Sentinel Quorum Monitoring & Client-Aware Automatic Failover in real Redis systems — specifically: Promote replica nodes automatically when a primary Redis host goes unreachable, so your code stays reliable, fast, and easy to maintain in production.
Redis Cluster 16,384 Hash Slots, {HashTags} & Live Slot Resharding
Purpose: To understand and apply Redis Cluster 16,384 Hash Slots, {HashTags} & Live Slot Resharding in real Redis systems — specifically: Scale write throughput horizontally and co-locate multi-key Lua operations via {tenantId} tags, so your code stays reliable, fast, and easy to maintain in production.
Redis 7 ACL Users, Protected Mode, TLS Encryption & SLOWLOG/Latency Doctor
Purpose: To understand and apply Redis 7 ACL Users, Protected Mode, TLS Encryption & SLOWLOG/Latency Doctor in real Redis systems — specifically: Lock down dangerous FLUSHALL/CONFIG commands and diagnose micro-stalls in production, so your code stays reliable, fast, and easy to maintain in production.
Solving Cache Stampede, Cache Penetration (Bloom/Null TTL) & Cache Avalanche (TTL Jitter)
Purpose: To understand and apply Solving Cache Stampede, Cache Penetration (Bloom/Null TTL) & Cache Avalanche (TTL Jitter) in real Redis systems — specifically: Keep databases protected when hot cached keys expire under 50,000+ concurrent requests, so your code stays reliable, fast, and easy to maintain in production.
Atomic Server-Side Lua Scripting & MULTI/EXEC/WATCH Optimistic Pipelines
Purpose: To understand and apply Atomic Server-Side Lua Scripting & MULTI/EXEC/WATCH Optimistic Pipelines in real Redis systems — specifically: Execute multi-step check-and-decrement logic atomically in sub-millisecond round trips, so your code stays reliable, fast, and easy to maintain in production.
Redis Streams Consumer Groups, Pending Entries (XPENDING/XAUTOCLAIM) & Dead-Letter Handling
Purpose: To understand and apply Redis Streams Consumer Groups, Pending Entries (XPENDING/XAUTOCLAIM) & Dead-Letter Handling in real Redis systems — specifically: Build durable, replayable event pipelines with guaranteed consumer crash recovery, so your code stays reliable, fast, and easy to maintain in production.
maxmemory Policies (allkeys-lru vs volatile-lfu), BigKey/HotKey Detection & Pipelining
Purpose: To understand and apply maxmemory Policies (allkeys-lru vs volatile-lfu), BigKey/HotKey Detection & Pipelining in real Redis systems — specifically: Prevent unexpected evictions and single-shard bottlenecks caused by oversized keys, so your code stays reliable, fast, and easy to maintain in production.
RDB vs AOF Persistence Trade-Offs, Redis Sentinel Failover & Cluster Hash Slots ({tag})
Purpose: To understand and apply RDB vs AOF Persistence Trade-Offs, Redis Sentinel Failover & Cluster Hash Slots ({tag}) in real Redis systems — specifically: Balance durability vs latency and co-locate multi-key operations safely on Redis Cluster, so your code stays reliable, fast, and easy to maintain in production.
Distributed Locking Pitfalls & Redis System Design Interview Scenarios
Purpose: To understand and apply Distributed Locking Pitfalls & Redis System Design Interview Scenarios in real Redis systems — specifically: Design global leaderboards, session stores, and real-time counters in senior interviews, so your code stays reliable, fast, and easy to maintain in production.