ES Index - S3 Snapshot & Restoration:

The question is. What brings you here? Fed up with all the searches on how to back-up and restore specific indices? 

Fear not, for your search quest ends here.!

After going through dozens of tiny gists and manual pages, here it is. We've done all the heavy lifting for you.



The following tutorial was tested on elasticsearch V5.4.0

And before we proceed, remember:

Do's:

Make sure that the elasticsearch version of the backed-up cluster/node <= Restoring Cluster's version.

Dont's:

Unless it's highly necessary;

        curl -X DELETE 'http://localhost:9200/nameOfTheIndex

              - deletes a specific index

Especially not, when you are drunk!:

        curl -X DELETE 'http://localhost:9200/_all

              - deletes all indexes (This is where the drunk part comes in..!!)



Step1: Install S3 plugin Support:

        sudo bin/elasticsearch-plugin install repository-s3
                                  (or)
        sudo /usr/share/elasticsearch/bin/elasticsearch-plugin install repository-s3

Depends on where your elasticsearch-plugin executable is installed. This enables the elasticsearch instance to communicate with the AWS S3 buckets.

Step2: Input the Snapshot registration settings:

METHOD: PUT

URL: http://localhost:9200/_snapshot/logs_backup?verify=false&pretty

PAYLOAD:
                {
                  "type": "s3",
                  "settings": {
                    "bucket": "WWWWWW",
                    "region": "us-east-1",
                    "access_key": "XXXXXX",
                    "secret_key": "YYYYYY"
                  }
                }


In the URL:
       - logs_backup: Name of the snapshot file

In the payload JSON:
        - bucket: "WWWWW" is where you enter the name of the bucket.
        - access_key & secret_key: The values "XXXXXX" and "YYYYYY" is where we key in the access key and secret key for the buckets based on the IAM policies - If you need any help to find it, here's a link which should guide you through (https://aws.amazon.com/blogs/security/wheres-my-secret-access-key/).
        - region: the region where the bucket is hosted (choose any from http://docs.aws.amazon.com/general/latest/gr/rande.html).

This should give a response as '{"acknowledged": "true"}'.

Step3: Cloud-Sync - list all Snapshots:

METHOD: GET 

URL: http://localhost:9200/_cat/snapshots/logs_backup?v


In the URL:
       - logs_backup: Name of the snapshot file
Time to sync up all the list of snapshots. If all our settings have been synced up just fine; we should end up with a list of indices, close to that of what is shown below:



  

Step4: Creating a Snapshot:

METHOD: PUT

URL: http://localhost:9200/_snapshot/logs_backup/type_of_the_backup?wait_for_completion=true

PAYLOAD:
            {
                "indices": "logstash-2017.11.21",
                "include_global_state": false,
                "compress": true,
                "encrypt": true
            }


In the URL:
       - logs_backup : Name of the snapshot file
       - type_of_the_backup : Could be any string
     
In the payload JSON:
        - indices: Correspond to the index which is to be backed-up to S3 bucket. In the case of multiple indices to back up under a single restoration point, the indices can be entered in the form of an array.
        - include_global_state: set to 'false' just to make sure there's cross-version compatibility. WARNING: If set to 'true', the index can be restored only to the ES of the source version.
        - compress: enables compression of the index meta files backed up to S3.
        - encrypt: In case if extra encryption on the indices is necessary.

This should give a response as '{"acknowledged": "true"}'

Step5: Restoring a Snapshot:

METHOD: PUT

URL: http://localhost:9200/_snapshot/name_of_the_backup/index_to_be_restored/_restore

PAYLOAD:
            {
                "ignore_unavailable": true,
                "include_global_state": false
            }

In the URL:
       - logs_backup: Name of the snapshot file
       - index_to_be_restored: Any of the index from the id listed in Step:3

In the payload JSON:
        - ignore_unavailable: It's safe to set this to true, to avoid unwanted checks.
        - include_global_state: set to 'false' just to make sure there's cross-version compatibility. WARNING: If set to 'true', the index can be restored only to the ES of the source version.

This should give a response as '{"acknowledged": "true"}'

Et Voila!  The restoration is complete.

And Don't forget to recycle the space corresponding to the index by safely deleting it - Reuse, Reduce & Recycle :)

Happy Wrangling!!!

Postgres to Mongo Migrator - Batteries Included!!!

DATABASE MIGRATION ACROSS PLATFORMS - Got your goosebumps yet?

     Well, long story short; cross-platform database migrations equals sleep talking, distress and long day works with coffee; and what good does it do? We will just end up writing hours and hours of scripts to conquer the end-result. However, It is of one-time-use-only, which lets you think to yourself; "All this horsepower and no room to gallop?".

Postgres to MongoDB:

    Be it a platform change, or maybe, it's due to the organizational growth or perhaps bad coding, or perhaps you have got your own microservices all set in, dwelling on the JSON objects; you might have had to switch from relational to noSQL databases. Switching can be tedious, I hear you and here lies the solution to all your worries.

Behold! Enter the Pg2Mongo:


 Pg2Mongo is an open source migration tool, written on pythonV3 which gives you an exclusive control over the migrations.

First Steps:

The initial step is to make sure you have access to both the Postgres and MongoDB servers. Upon cloning the repository, make sure you install the requirements for the pg2mongo to run.


For demonstration-sake, let's try to migrate the dataset provided along with the pg2mongo for us to play-around.

Configuration setup:

And now, all we got to do is to set up the instructions for the migrator to wrangle. The configuration file is at the location - 'pg2mongo/pg2mongo.yml' and it goes as follows:

The preliminary sections such as extraction and commit are self expanatory, stating the configuration settings for the extraction and commit databases. The component Migration is where all the magic happens!

The following section explains what the individual components are all about:

INIT_TABLE:

Inital table from which data needs to be migrated. This could be a prime table such as a transactions table with a primary key having multiple foreign constraints to other tables of the postgreSQL database. FOR EACH ENTRY IN THIS TABLE, THE LINKING OF OTHER TABLES WILL HAPPEN WHILE DEFINING THE TABLES.

INIT_KEYS:

KEYS of the init_table (aliases can be given using 'as')

SKELETON:

Skeleton is an empty raw python dictionary assignment which will transform to a mongodb document, upon migration

TABLES_ORDER:
 
The order by which the TABLES section needs to be executed for each of the entry from INIT_TABLE

TABLES:

Set of PostgreSQL tables enlisted along with condition and corresponding mapping. In the case of lists inside a dictionary, list can be mentioned. Mapping is where, the association of skeleton to the table keys is defined. The value assignments are python compatible; hence, they are defined by using '%s' and other python based variable transformation functions can be used over here.

COLLECTIONS:

This is where the push of the skeleton to the corresponding MongoDB collection takes place.
With all the instructions in place, it's time to wrangle. You may invoke the migration by keying in the following command.
And off she goes!!


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