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Most important sections
- Parquet: data format used by Apache Spark;
- Password spray: hacking technique. You try the most common passwords on multiple accounts, trying to find an account that used that password;
- SIM-jacking: vulnerability that uses SIMs and SMS content;
- Hammering: hacking technique. Hackers send continuous push notifications until the victim, annoyed by these notifications, accepts one and gives permissions to the intruder;
- Adversary-in-the-middle: deceive users;
- DAPR: used for Sidecar architecture. The main application communicates with the sidecar via GRPC or HTTP;
- Fitness Functions: functions that check the -ilities of the architecture. You use metrics and monitors;
- ArchUnitNET: library for testing the code architecture. You can validate the modules dependencies;
- JIT (Just-in-time compilation): compiles the code on the fly; it compiles the code that you are going to execute;
- OSR (On-stack replacement): used to optimize methods with long runs. If during the first executions it finds something to optimize, it replaces the low-level code on the stack;
- Dynamic PGO: the Jitter understands the code usage and optimizes the compilation;
- SNAT (source network address translation): SNAT maps the IP address of the backend to the public IP address of your load balancer. SNAT prevents outside sources from having a direct address to the backend instances;
- B-tree: data structure used for indexing in SQL databases;
- Rowstore index: index based on the value of the row. Userful for searches for specific values or ranges;
- Columnstore index: index based on the values for a specific column. It's a
distincton the values on the column, and is useful for searching for multiple rows with the same value in that column. You can even use an index on every column; it is optimized for reads; it is useful for creating reports;
- Heap (SQL): column without indexes;
- Graph on SQL server: you can create graphs using
CREATE TABLE AS EDGEand
CREATE TABLE AS NODE;
- Clustered-index on a date makes the database equivalent to a time-series database;
- RLS (Row-level security): based on the user executing the query, the query can view a subset of the rows. It happens using a Tabular function that, given the user, returns the subset of the rows. This subset is then optimized by the DB engine. A good usage is multi-tenant applications, where you don't want data leak to other companies. Also known as Policy-Based Security.
- Data masking: the database masks sensible data automatically, so that developers (and log tools) cannot access the data. To see the actual value you have to execute an
- Ledger: to entrust that data has not been changed from a specific date, all the updates on the main db are also stored on a separate read-only database. In this way, by checking the final outcome, you can demonstrate that data has not been tampered;
- Data API builder: dotnet tool that generates CRUD APIS (Rest or GraphQL) for a table on the Azure Database. It also handles pagination, authentication, filtering...
- Hyperscale: SQL engine used to perform queries on distributed databases. Data is also stored in-memory for faster access.