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Storage Topics

Here’s a logical progression of topics that fall under the storage domain, organized in a way that builds foundational knowledge before moving to more advanced concepts. This outline will help you understand how to approach storage systems, from basic to complex, covering topics applicable to both traditional and distributed storage environments.

1. Basic Storage Concepts

  • Introduction to Data Storage:
    • Definition of storage.
    • Types of storage (primary, secondary, tertiary).
    • Overview of storage devices (HDD, SSD, optical, tape).
  • File Storage vs Block Storage vs Object Storage:
    • Understanding file-level storage (hierarchical structure, files and directories).
    • Block storage (fixed-size blocks, used in SANs).
    • Object storage (data stored as objects with metadata, used in cloud storage).
  • Storage Interfaces:
    • SATA, SAS, NVMe, USB.
    • Storage network protocols: iSCSI, Fibre Channel, NFS, SMB/CIFS.
  • Disk Partitioning:
    • What is partitioning?
    • Partitioning schemes (MBR vs GPT).
    • Basic partitioning tools: fdisk, parted.

2. File Systems

  • Introduction to File Systems:
    • What is a file system?
    • Functions of a file system (organizing files, managing storage, access control).
  • Common File Systems:
    • ext2/ext3/ext4 (default in Linux).
    • NTFS, FAT32/exFAT (used in Windows).
    • XFS (used in high-performance environments).
    • Btrfs (with advanced features like snapshots and subvolumes).
    • ZFS (used for scalability, redundancy, snapshots).
  • Mounting and Unmounting File Systems:
    • Understanding mount points.
    • Tools for mounting: mount, umount.
    • /etc/fstab configuration for persistent mounts.

3. Disk Management

  • Logical Volume Management (LVM):
    • What is LVM?
    • Benefits of using LVM (flexibility in resizing, snapshots).
    • LVM components: physical volumes, volume groups, logical volumes.
    • Basic LVM commands: pvcreate, vgcreate, lvcreate, lvextend, lvreduce.
  • RAID (Redundant Array of Independent Disks):
    • What is RAID?
    • RAID levels: RAID 0 (striping), RAID 1 (mirroring), RAID 5, RAID 6, RAID 10.
    • Software RAID vs Hardware RAID.
    • RAID tools in Linux: mdadm.
  • Disk Quotas:
    • Implementing quotas to manage disk usage by users.
    • Tools: quota, edquota.

4. Data Redundancy and Backup

  • Replication:
    • What is replication?
    • Synchronous vs asynchronous replication.
    • File-level replication vs block-level replication.
    • Tools for replication: rsync, DRBD (block-level replication), MySQL replication (for databases).
  • Backups:
    • Types of backups: full, incremental, differential.
    • Backup strategies: 3-2-1 rule (3 copies, 2 local, 1 offsite).
    • Backup tools: rsnapshot, Duplicity, Bacula.
    • Snapshot-based backups (e.g., ZFS snapshots, LVM snapshots).

5. Advanced File Systems and Storage Technologies

  • ZFS:
    • Introduction to ZFS.
    • Features of ZFS: snapshots, replication, checksumming, RAID-Z.
    • Managing ZFS: zpool, zfs commands.
  • Btrfs:
    • Introduction to Btrfs.
    • Btrfs features: snapshots, subvolumes, compression.
    • Managing Btrfs: btrfs commands.
  • Ceph Distributed Storage:
    • Introduction to Ceph (distributed, scalable storage system).
    • Ceph architecture: Monitors (MON), Object Storage Daemons (OSD), CephFS, RADOS Gateway.
    • Ceph storage types: block storage (RBD), object storage, file storage.
  • GlusterFS:
    • Introduction to GlusterFS (distributed file system).
    • Features of GlusterFS: scaling out storage, fault tolerance, real-time replication.
    • Setting up GlusterFS clusters.

6. Storage Virtualization

  • Storage Virtualization Concepts:
    • Introduction to storage virtualization.
    • Benefits of virtualized storage: abstraction, scalability, management.
    • Types: Block-level virtualization (SAN), file-level virtualization (NAS).
  • Virtual Disks:
    • Understanding virtual disks in virtualization environments (e.g., VMware, KVM).
    • Creating and managing virtual disk images (qcow2, vmdk, raw formats).
  • Persistent Storage for Containers:
    • Managing persistent storage for Docker and Kubernetes.
    • Volumes and persistent volume claims in Kubernetes.
    • CSI (Container Storage Interface) for connecting storage to Kubernetes.

7. Storage in Cloud and Distributed Environments

  • Object Storage:
    • Introduction to object storage systems (e.g., Amazon S3, OpenStack Swift).
    • Characteristics of object storage (scalability, flat namespace).
    • Access protocols (S3 API, Swift API).
  • Cloud Storage Solutions:
    • Comparing cloud storage services (Amazon S3, Google Cloud Storage, Azure Blob Storage).
    • Cloud storage models: IaaS, PaaS, SaaS.
  • Storage in Distributed Systems:
    • CAP theorem and its relation to storage (Consistency, Availability, Partition Tolerance).
    • Distributed file systems (e.g., Hadoop HDFS, GlusterFS, Ceph).
  • Erasure Coding:
    • Understanding erasure coding as a method for data redundancy.
    • Comparison to replication (efficient use of space).

8. Data Integrity, Security, and Compression

  • Data Integrity:
    • Techniques to ensure data integrity (checksums, error detection).
    • Tools: ZFS checksums, Btrfs data integrity features.
  • Encryption and Security:
    • Encrypting data at rest and in transit.
    • Tools for encryption: LUKS (Linux Unified Key Setup), dm-crypt.
    • Secure file transfer: SCP, SFTP.
  • Data Compression:
    • Compressing data to save storage space.
    • File system-level compression: ZFS, Btrfs.
    • Tools: gzip, bzip2, xz.

9. Storage Performance Tuning

  • I/O Performance Metrics:
    • Understanding IOPS, throughput, and latency.
    • Tools for measuring performance: iostat, fio, hdparm.
  • Caching Mechanisms:
    • Disk caching and write-back vs write-through caching.
    • Tools for managing cache: bcache, dm-cache.
  • Tuning File Systems:
    • Optimizing ext4, XFS, or ZFS for specific workloads.
    • Mount options for performance: noatime, nodiratime, etc.
  • SSD Optimization:
    • Managing SSD wear and performance.
    • Tools: fstrim, SSD over-provisioning.

10. Disaster Recovery and High Availability

  • Disaster Recovery Strategies:
    • Creating DR plans.
    • Recovery time objectives (RTO) and recovery point objectives (RPO).
  • High Availability Storage:
    • Tools and techniques for high availability: RAID, replication, Ceph/GlusterFS.
    • Failover mechanisms: Pacemaker + DRBD, MySQL Galera Cluster.

Conclusion: Putting It All Together

  • Building a Storage Infrastructure:
    • Designing storage solutions based on workload, capacity, performance, and scalability needs.
    • Combining technologies (RAID, LVM, file systems) to create resilient storage systems.
    • Deploying distributed storage for scalability and high availability.

This structured outline takes you from the basics of data storage to advanced topics like distributed storage systems, performance tuning, and disaster recovery. By following this path, you’ll develop a comprehensive understanding of storage technologies and how they are applied in various environments.

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