# mon Published articles for mon. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Recover the Ceph Monitor Store Using OSDs DevFeed: [Recover the Ceph Monitor Store Using OSDs]() Original publisher: [Read original article]() Author: Eugen Block, crossposted by Anthony D'Atri Published: 2026-07-04T00:00:00Z Content type: article Language: en Sources: [Ceph Blog]() Topics: [ceph](), [monitor](), [Script](), [Containers](), [log management]() Tags: [blog](), [blog-post](), [ceph](), [containers](), [en-article](), [en-blog-post](), [how-to](), [logging](), [logs](), [mon](), [monitor](), [recovery]() ### AI overview This blog post presents a general procedure for recovering a failed Ceph Monitor store by collecting osdmaps from existing OSDs, with additional considerations for cephadm-managed container deployments. It automates osdmap collection and basic logging while leaving the store rebuild and client authentication steps for careful manual inspection. The procedure applies only to non-encrypted OSDs, and the article emphasizes the importance of backing up dmcrypt/LUKS keys and reviewing host logs. ### Source excerpt Introduction ¶ A few weeks ago I helped a Ceph user to recover his broken cluster (see this thread). Basically, after his Monitors stopped working he re-deployed a new cluster with the same Ceph FSID and attached the existing OSDs to the re-deployed hosts. But it's not that easy to re-activate those OSDs because the new Monitors don't have the old osdmap, hence they don't know anything about the existing OSDs. So how did we fix that? This scenario can be considered a total Monitor store failure. There's a documented procedure in the upstream docs, unfortunately it's written for non-cephadm clusters and doesn't contain many details about subsequent steps. When Ceph daemons run within containers there are more things to consider. So I decided to write this blog post and add some more details to the procedure, targeting mainly clusters managed by cephadm. But the recovery procedure doesn't specifically require cephadm-specific commands, so it can be considered as a general guideline how to recover from a Monitor store loss, just with some extra details about cephadm deployments. This procedure only works for non-encrypted OSDs. If you are using dmcrypt (LUKS) OSDs, make sure you have a backup of the keys, otherwise your data is lost forever! But there is some development, a user in Slack pointed me to this PR which adds a backup mechanism for Monitors, probably available in the upcoming Umbrella release. Note that the PR also contains this statement: Monitor backups complement, but do not replace, the existing Monitor recovery procedures The procedure covered by said docs is already written in script form, so I used that as a template and extended it for cephadm usage and included some very basic logging. It collects the osdmaps from all OSDs and contains the necessary considerations regarding containers. I decided to automate only the osdmap collection, not all required steps of the store rebuild procedure (e. g. Monitor store rebuild, client auth, etc.) because the r ## RocksDB Compression in Ceph: Space Savings with No Performance Cost DevFeed: [RocksDB Compression in Ceph: Space Savings with No Performance Cost]() Original publisher: [Read original article]() Author: Daniel Alexander Parkes, Anthony D'Atri Published: 2025-12-17T00:00:00Z Content type: article Language: en Sources: [Ceph Blog]() Topics: [Compression](), [Database](), [Hardware](), [ibm]() Tags: [blog-post](), [ceph](), [compression](), [configuration](), [cost](), [devices](), [en-article](), [en-blog-post](), [ibm](), [mon](), [nvme](), [osd](), [performance](), [rados](), [reef](), [rocksdb](), [space](), [storage]() ### AI overview This article reports Ceph performance tests showing that enabling RocksDB compression can substantially reduce metadata database space, especially for smaller objects, without harming throughput or resource consumption. The tests used IBM Storage Ceph 7.1 with BlueStore OSDs, HDD object storage, and NVMe devices for the RocksDB WAL and database. ### Source excerpt Introduction ¶ In the world of data storage, engineers and architects constantly face a fundamental dilemma: the trade-off between performance and efficiency. It's a balancing act. When you want to save space, you typically enable features like compression, but the common assumption is that this will cost you performance, a CPU cycle tax that slows throughput. But what if you could significantly reduce your metadata storage footprint without slowing things down? This search for an answer to this question started with research work from Mark Nelson, who published a blog post on ceph.io that covers RocksDB tuning in depth, exploring RocksDB compression with positive results. These promising results sparked a conversation on the upstream GitHub about enabling compression by default; a link to the PR is available here. To build on the previous investigation, the Ceph performance team ran tests on a robust hardware configuration running IBM Storage Ceph 7.1 (Reef). The cluster used the BlueStore OSDs for an erasure-coded (EC 4+2) pool, with a hybrid OSD storage setup: HDDs for object data and fast NVMe drives for the BlueStore WAL+DB. To understand the test, it's helpful to know what the WAL+DB is. In modern Ceph, the BlueStore storage engine manages all data on the OSDs (physical devices). To do this, it must maintain a vast catalog of internal metadata: think of it as a high-speed index that quickly locates every piece of data. RocksDB, a high-performance key-value database, manages this critical index. In our hybrid cluster, the RocksDB database runs on the fast NVMe deviceses, while the actual object data resides on the slower HDDs. Because this metadata can grow very large, RocksDB's efficiency, how much space it consumes on those expensive NVMe drives, is a critical factor in the cluster's overall cost and performance. Our test, therefore, focuses on a simple, high-stakes question: Can we compress this metadata to save space without paying a performance penalty? Ex