Mark Paluch

Mark Paluch

Mark is Software Craftsman, Spring Data Project Lead at Pivotal, and Lead of the Lettuce Redis driver. His focus is now on reactive data integrations and R2DBC.

Recent Blog posts by Mark Paluch

Spring Data Release Train Ingalls M1 Released

Releases | July 27, 2016 | ...

On behalf of the Spring Data team, I’m happy to announce the first milestone of the Ingalls release train. The release ships 230 tickets fixed! The most noteworthy new features are:

  • Use of method handles for property access in conversion subsystem (Commons, MongoDB).
  • Upgrade to Cassandra 3.0 for Spring Data Cassandra (see the updated examples for details).
  • Support for declarative query methods for Cassandra repositories.
  • Support for Redis geo commands.
  • Any-match mode for query-by-example.
  • Support for XML and JSON based projections for REST payloads (see the example for details)

Find a curated change log in our release train wiki or skim through a full list of changes in JIRA

Managing Secrets with Vault

Engineering | June 24, 2016 | ...

Passwords, API keys and confidential data fall into the category of secrets. Storing secrets the secure way is a challenge with limiting access and a true secure storage. Let's take a look at Hashicorp Vault and how you can use it to store and access secrets.

How do you store Secrets?

Passwords, API keys, secure Tokens, and confidential data fall into the category of secrets. That's data which shouldn't lie around. It mustn't be available in plaintext in easy to guess locations. In fact, it must not be stored in plaintext in any location.

Sensitive data can be encrypted by using the Spring Cloud Config Server or TomEE. Encrypted data is one step better than unencrypted. Encryption imposes on the other side the need for decryption on the user side which requires a decryption key to be distributed. Now, where do you put the key? Is the key protected by a passphrase? Where do you put the passphrase? On how many systems do you distribute…

Spring Data release train Hopper SR2 released

Releases | June 15, 2016 | ...

On behalf of the Spring Data team I’d like to announce the availability of the second service release of the Spring Data Hopper release train. The release ships 103 issues fixed. We fixed a couple of bugs in the area of repository projections, especially for JPA users and introduce Hibernate 5.2 compatibility with this release (also already back-ported to the Gosling release train for inclusion in the upcoming service release). Hopper SR2 is a recommended upgrade for all Hopper users and also users of previous release trains.

Here are the released modules:

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