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Displaying posts with tag: storage (reset)
Got open source cloud storage? Red Hat buys Gluster

Red Hat’s $136m acquisition of open source storage vendor Gluster marks Red Hat’s biggest buy since JBoss and starts the fourth quarter with a very intersting deal. The acquisition is definitely good for Red Hat since it bolsters its Cloud Forms IaaS and OpenShift PaaS technology and strategy with storage, which is often the starting point for enterprise and service provider cloud computing deployments. The acquisition also gives Red Hat another weapon in its fight against VMware, Microsoft and others, including OpenStack, of which Gluster is a member (more on that further down). The deal is also good for Gluster given the sizeable price Red Hat is paying for the provider of open source, software-based, scale-out storage for unstructured data and also as validation of both open source and software in today’s IT and cloud computing storage.

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zfs FileSystem and MySQL




ZFS is a new kind of 128-bit file system that provides simple administration, transactional semantics, end-to-end data integrity, and immense scalability. ZFS is not an incremental improvement to existing technology; it is a fundamentally new approach to data management. ZFS was first introduced in Solaris in 2004 and it is a default filesystem in OpenSolaris, but Linux ports are underway, Apple is shipping it in OS X 10.5 Leopard with limited zfs capability ( Apple shutdown this project afterward due to some known reason), and it will be included in FreeBSD 7.
ZFS Features:

  • Pooled Storage Model
  • Always consistent on disk
  • Protection from data corruption
  • Live data scrubbing
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RE: A bit on SANs and system dependencies

This is a reply on A bit on SANs and system dependencies by Eric Bergen.

Lets first start by making a difference between entry level, midrange and high-end SAN's.

Entry level:
This is basically a bunch of disks with a network connection. The Oracle/Sun/StorageTek 2540 is an example for this category. This storage is aimed at lowcost shared storage.

Midrange:
This kind of storage generally features replication and more disks than entry level. HP EVA is what comes to mind for this category. This storage is aimed at a good price/performance.

High-End:
This is mainframe style storage which is made usable for open systems. Hitachi Data Systems VSP is a good example of this category. This category is for extreme performance and reliability. …

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OpenDBCamp: Information Lifecycle Architecture

The Open DB Camp in Sardinia 2011 has had a number of sessions on varying topics. Topics range from MySQL over MongoDB to replication and High Availability.

I decided to tap into the database expert resources present here at Sardegna Ricerche by discussing a non-database issue, where one can expert database experts to have insights beyond those of end users. And they did.

The topic was the particular case of information overload many of us suffer from on our hard disks: Too many files, too hard to find.

  • How do we find the bank statement from April 2007 from the more-seldom-used account?
  • What are the ten best work-related pictures from last year?
  • Is this the most current …
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Roll Your Own Cloud (from linux.conf.au 2011)

At linux.conf.au 2011 in Brisbane, I had the honor of co-presenting a talk on Rolling Your Own Cloud with SUSE’s Tim Serong. Take a look!


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Tech Messages | 2011-01-15

A special extended edition of Tech Messages for 2011-01-12 through 2011-01-15:

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DRBD != fsck != DIX

Every once in a while, we hear of users with corruption in a file system that sits on top of DRBD. That may be easy or tricky to resolve. If you’re lucky, a simple fsck will resolve the corruption. If you’re not quite that lucky, you may have to get out your backups.

But that’s typically not DRBD’s fault. Typically not at all, not in the least bit. DRBD is a block device, and as such it has no idea what rests on top of it. It has no concept of a filesystem, let alone its integrity. That of course is true for any other block device as well. If you have, say, RAID-1, and something corrupts the file system on top of it, then of course that corruption will be happily replicated across both component devices. DRBD is no different, except that its component devices are stored across distinct physical nodes.

And even if everything about your filesystem is logically correct, there’s still the chance that a …

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LCA Miniconf Call for Papers: Data Storage: Databases, Filesystems, Cloud Storage, SQL and NoSQL

This miniconf aims to cover many of the current methods of data storage and retrieval and attempt to bring order to the universe. We’re aiming to cover what various systems do, what the latest developments are and what you should use for various applications.

We aim for talks from developers of and developers using the software in question.

Aiming for some combination of: PostgreSQL, Drizzle, MySQL, XFS, ext[34], Swift (open source cloud storage, part of OpenStack), memcached, TokyoCabinet, TDB/CTDB, CouchDB, MongoDB, Cassandra, HBase….. and more!

Call for Papers open NOW (Until 22nd October).

ScaleDB Cache Accelerator Server (CAS): A Game Changer for Clustered Databases

ScaleDB and Oracle RAC are both clustered databases that use a shared-disk architecture. As I have mentioned previously, they both actually share data via a shared cache, so it might be more appropriate to call them shared-cache databases.

Whether it is called shared-disk or shared-cache, these databases must orchestrate the sharing of a single set of data amongst multiple nodes. This introduces two challenges: the physical sharing of the data and the logical sharing of the data.

Physical Sharing:
Raw storage is meant to work on a 1:1 basis with a single server. In order to share that data amongst multiple servers, you need either a Network File System (NFS), which shares whole files, or a Cluster File System (CFS), which shares data blocks.

Logical Sharing:
This is specific to …

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No, DRBD doesn’t magically make your application crash safe

It is a common misconception that DRBD (or any block-level data replication) solution can magically make an application crash-safe that intrinsically isn’t. Baron highlights that misconception in a recent blog post.

I want to reiterate and stress that point here: if your application can’t reliably survive a node crash, it won’t successfully fail over on a replicated (or shared, for that matter) data device. But if it can, and DRBD is replicating synchronously, then DRBD won’t break it. In other words: try pulling the power plug on your machine while your app is running, and power back on. If your application recovers to a consistent state, you’re clear. If it doesn’t, don’t bother adding DRBD until you fix that.

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