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Replace master branch with main in documentations
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documentation/sphinx/source/architecture.rst

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evenly distributed across all storage servers (SS). Data distributor as
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a singleton in the cluster is recruited and monitored by Cluster
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Controller. See `internal
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documentation <https://github.com/apple/foundationdb/blob/master/design/data-distributor-internals.md>`__.
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documentation <https://github.com/apple/foundationdb/blob/main/design/data-distributor-internals.md>`__.
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Ratekeeper
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~~~~~~~~~~
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system is recruited, the Master writes the coordinated states with current
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transaction system information. Finally, the Master accepts new
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transaction commits. See details in this
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`documentation <https://github.com/apple/foundationdb/blob/master/design/recovery-internals.md>`__.
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`documentation <https://github.com/apple/foundationdb/blob/main/design/recovery-internals.md>`__.
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Because GRV Proxies, Commit Proxies and Resolvers are stateless, their
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recoveries have no extra work. In contrast, Transaction Logs save the
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Post <https://forums.foundationdb.org/t/technical-overview-of-the-database/135/26>`__
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`Existing Architecture
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Documentation <https://github.com/apple/foundationdb/blob/master/documentation/sphinx/source/kv-architecture.rst>`__
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Documentation <https://github.com/apple/foundationdb/blob/main/documentation/sphinx/source/kv-architecture.rst>`__
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`Summit
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Presentation <https://www.youtube.com/watch?list=PLbzoR-pLrL6q7uYN-94-p_-Q3hyAmpI7o&v=EMwhsGsxfPU&feature=emb_logo>`__
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`Data Distribution
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Documentation <https://github.com/apple/foundationdb/blob/master/design/data-distributor-internals.md>`__
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Documentation <https://github.com/apple/foundationdb/blob/main/design/data-distributor-internals.md>`__
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`Recovery
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Documentation <https://github.com/apple/foundationdb/blob/master/design/recovery-internals.md>`__
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Documentation <https://github.com/apple/foundationdb/blob/main/design/recovery-internals.md>`__
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.. |image0| image:: images/Architecture.png
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.. |image1| image:: images/architecture-1.jpeg

documentation/sphinx/source/release-notes/release-notes-700.rst

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* Added TLS support to fdbdecode for decoding mutation log files stored in blobs. `(PR #4611) <https://github.com/apple/foundationdb/pull/4611>`_
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* Added ``initial_snapshot_interval`` to fdbbackup that can specify the duration of the first inconsistent snapshot written to the backup. `(PR #4620) <https://github.com/apple/foundationdb/pull/4620>`_
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* Added ``inconsistent_snapshot_only`` to fdbbackup that ignores mutation log files and only uses range files during the restore to speedup the process. `(PR #4704) <https://github.com/apple/foundationdb/pull/4704>`_
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* Added the Testing Storage Server (TSS), which allows FoundationDB to run an "untrusted" storage engine with identical workload to the current storage engine, with zero impact on durability or correctness, and minimal impact on performance. `(Documentation) <https://github.com/apple/foundationdb/blob/master/documentation/sphinx/source/tss.rst>`_ `(PR #4556) <https://github.com/apple/foundationdb/pull/4556>`_
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* Added the Testing Storage Server (TSS), which allows FoundationDB to run an "untrusted" storage engine with identical workload to the current storage engine, with zero impact on durability or correctness, and minimal impact on performance. `(Documentation) <https://github.com/apple/foundationdb/blob/main/documentation/sphinx/source/tss.rst>`_ `(PR #4556) <https://github.com/apple/foundationdb/pull/4556>`_
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* Added perpetual storage wiggle that supports less impactful B-trees recreation and data migration. These will also be used for deploying the Testing Storage Server which compares 2 storage engines' results. See :ref:`Documentation <perpetual-storage-wiggle>` for details. `(PR #4838) <https://github.com/apple/foundationdb/pull/4838>`_
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* Improved the efficiency with which storage servers replicate data between themselves. `(PR #5017) <https://github.com/apple/foundationdb/pull/5017>`_
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* Added support to ``exclude command`` to exclude based on locality match. `(PR #5113) <https://github.com/apple/foundationdb/pull/5113>`_

documentation/sphinx/source/transaction-profiler-analyzer.rst

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There are many ways that this data can be exposed for analysis. One can imagine building a client that reads the data from the database and streams it to external tools such as Wavefront.
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One such tool that’s available as part of open source FDB is a python script called ``transaction_profiling_analyzer.py`` that's available here on `GitHUb <https://github.com/apple/foundationdb/blob/master/contrib/transaction_profiling_analyzer/transaction_profiling_analyzer.py>`_. It reads the sampled data from the database and outputs it in a user friendly format. Currently it’s most useful in identifying hot key-ranges (for both reading and writing).
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One such tool that’s available as part of open source FDB is a python script called ``transaction_profiling_analyzer.py`` that's available here on `GitHUb <https://github.com/apple/foundationdb/blob/main/contrib/transaction_profiling_analyzer/transaction_profiling_analyzer.py>`_. It reads the sampled data from the database and outputs it in a user friendly format. Currently it’s most useful in identifying hot key-ranges (for both reading and writing).
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Prerequisites
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=============

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