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Hashing is one-way for verification, while encryption is two-way for confidentiality.

Encryption at rest and in transit are essential for protecting data both stored and in motion.

Secure API design requires multiple strategies to protect sensitive data and access.

Authentication verifies who you are, while authorization determines what you can do.

Data residency is crucial for compliance with laws about where data can be stored.

HTTPS is a secure version of HTTP that encrypts data for safety.

Symmetric encryption uses one key, while asymmetric uses a pair of keys for security.

KMS securely manages encryption keys to protect data from theft.

The TLS handshake establishes a secure connection for HTTPS, ensuring data safety.

OAuth 2.0 lets apps access user data securely without passwords.

Session-based authentication uses cookies to remember users after login.

Password hashing with unique salts ensures security by creating different hashes for identical passwords.

SSRF is a vulnerability where an attacker tricks a server into making unintended requests.

API keys help identify clients and control their access to APIs securely.

Zero Trust Architecture ensures that no user or device is trusted by default.

CSRF tricks your browser into making requests without your consent.

XSS is a vulnerability that lets attackers run scripts in users' browsers.

SQL injection is a security risk where attackers manipulate database queries via input fields.

Database isolation levels determine how transactions interact and affect data consistency.

Database per Service ensures each microservice owns its data, reducing dependencies.

Fail Fast means stopping quickly on errors, while Fail Safe ensures safety in failures.

Cache penetration occurs when requests for non-existent data overload the database.

Backup strategies include Full, Incremental, and Differential, each with unique benefits.

mTLS allows microservices to verify each other's identities using certificates.

Data lakes store large volumes of diverse data for analytics and processing.

Availability is about access; reliability is about correct performance.

Cassandra uses a masterless architecture to distribute and replicate data efficiently.

Transactions ensure database operations are reliable using ACID properties.

The CAP Theorem explains the trade-offs in distributed systems during network failures.

Token expiration and refresh token rotation secure user sessions by limiting token lifespan and preventing unauthorized access.

The Bulkhead Pattern isolates resources to protect critical workloads from failures.

Functional requirements define what a system does, while non-functional requirements define how it performs.

JWTs allow secure user authentication without needing session storage.

Access tokens are short-lived tokens for API access, while refresh tokens renew them without re-login.

Disaster recovery ensures systems can restore services and data after major disruptions.

OLTP handles transactions while OLAP is for data analysis and reporting.

Sharding splits databases into smaller parts to improve performance and scalability.

Stateless servers are easier to scale because they don't store user session data locally.

Optimistic and pessimistic locking are strategies to manage database access during concurrent transactions.

2-Phase Commit helps maintain data consistency in transactions across multiple databases.

Choosing the right boundaries for microservices is crucial for effective architecture.

Multi-region data consistency ensures that users in different locations see the same data.

Retention policies help manage how long data is kept in databases.

Dynamo-style databases are designed for high availability and fault tolerance in distributed systems.

Protobuf schema evolution requires careful changes to avoid breaking existing clients.

OpenID Connect allows apps to authenticate users and verify their identities securely.

Consistent hashing helps distribute data across servers with minimal movement.

Data warehouses help businesses analyze large amounts of data for better decision-making.

Data Lakehouse architecture merges flexible data storage with reliable analytics capabilities.

The choice between SQL and NoSQL databases depends on your application's specific needs.

Cassandra uses clustering keys to sort rows within a partition for efficient querying.

REST API design focuses on creating clean, efficient, and scalable web services.

Write-Ahead Log ensures data is safely recorded before changes are made.

MongoDB uses replica sets for data redundancy and sharding for scalability.

RPO and RTO are key metrics for planning disaster recovery strategies.

Cassandra uses partition keys to determine how and where to store data across nodes.

Observability helps engineers understand system behavior to debug production issues effectively.

Change Data Capture allows real-time syncing of database changes to other systems.

Distributed locks ensure only one server performs a task, avoiding duplication.

Choosing the right labels in time-series data is crucial to avoid inefficiencies.