1. Comparing to something like GitPod (which lets you run on your own instances as well), where do you think Hocus shines?
2. Given you're leveraging Firecracker for isolation, and Firecracker doesn't support GPUs, I assume that adding GPU-enabled machines isn't on your near-term roadmap?
Okera | San Francisco (SF) and Seattle (REMOTE considered for the right candidate) | Full-time, VISA
Okera opens up data for greater innovation by scaling access and governance across heterogeneous, distributed data environments. The Okera Active Data Access Platform manages data access across a multi-cloud, multi-datastore and multi-tool world reducing friction between agility and governance. With greater accessibility, protection and visibility, you have the confidence to move forward to innovate.
Your data can do more. It can be used by analysts and data scientists to drive innovation. It can help you discover untapped markets, unseen opportunities, and unproductive workflows. It can change the way your business and the world works.
The Okera platform tackles the hardest issues behind data access and governance across hybrid and multi-cloud environments—giving you the ability to explore your data’s potential like never before. Our vision is to enable self-service analytics with responsible data access so that everyone can benefit from the potential of data in the enterprise.
Open positions include:
* Staff Backend Software Engineer - Data Platforms (San Francisco or Seattle)
* Staff Backend Software Engineer - Data Platforms
* Staff Frontend Software Engineer (San Francisco or Seattle)
* Senior or Staff Frontend Software Engineer
* Staff DevOps Engineer
* Director of Product
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Backend Tech Stack: Java, Go, C++, Kubernetes and the big data ecosystem (Spark, Presto, Hive, Impala, etc)
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Questions? Contact myself (email in profile) or Chris via email: [email protected] or apply online! You can read more about us at https://www.okera.com as well.
We're a big Atlassian shop, and switched from Crucible to Bitbucket Server (then Stash). I do not get the sense that Crucible is the future as far as Atlassian is concerned - I believe they see Bitbucket Server as what they are going to focus on.
FWIW, with the latest releases, they've addressed most of the remaining features that were missing from Crucible, and I'm very happy now with the PR/code review flow in Bitbucket Server.
I've been trying to figure this out from the docs, but how does it support Windows? In the sense that for now (until Server 2016 comes out), you don't really have "container support".
Honest non-troll question: when you say high-performance, what's the measurement? I'm honestly curious what the right benchmark is for a DB like this, especially one that's doing a variety of spatial queries.
I'm specifically interested in how the measurement performs with a lot of writes constantly happening.
We were early adopters of the API, and we still use it to demo integration of Splunk with 3rd party dashboards.
The beauty of the API is that it allows you to display relatively arbitrary data in very compelling ways.
For example, we have access to quite a bit of data at Splunk, from Twitter, server logs, etc. A lot of our customers ask us how they can use the data that is inside Splunk and present it in a 3rd-party dashboard, so we built a demo with Leftronic.
Yes, that's my understanding as well. That's also what I want. I'm taking a snapshot in time of a page, so that I can then go back to that snapshot and look at it.
Sometimes those snapshots are not valuable after a while, so I delete them :)
I'm not quite sure what you mean. Your clips can be private and shared with a few people (or none), or they can be completely public. In the example I gave, I wouldn't really mind if they were public, but I don't see a reason to make them public - it is just to share with a few friends, really.
In my opinion: you're clipping content + structure, and not just something like images/text. So you get to preserve the original layout, links, etc, which is a huge benefit.
You can also have things private and/or shared with a select group of people, which is what I usually do.
For example, a common use case I've found is that I'll clip something from Gilt/other signup required sites, to show someone a deal they might be interested in, but they don't want to sign up just to look at it. If they like it, they end up signing up.
I've been using Clipboard for a long time now, and know several people who built the site. It's an amazing team and they did an amazing job with it. It would be easy to be discouraged with hotness of Pinterest, but they're going at it from a different, very valuable direction.
Seattle, San Francisco, Cupertino (and other places), FULL-TIME, INTERN, H1B
A lot of people think Splunk must be a terrible place to work at because they think it is an "enterprise" company. But the truth is, we have great jobs for a lot of people.
Want to work on awesome visualizations for gigabytes and terabytes of data daily? We got it. Want to work on building a development platform for an extremely powerful data analysis tool? We got it. Want to help make the core server that powers our extremely fast indexing and performance better? We got it.
For example, my project for the past couple of months has been to develop our new Node.js/Browser SDK, including pulling some of our propietary UI components and sharing them with the world. We also do a lot of work with customers to best help them use Splunk. One of the projects I was involved in included analyzing social data using Splunk (like Twitter/Foursquare).
Whether it's UI, core systems engineering, dev platform or anything in between, we likely have something for you. I personally work on the development platform in the Seattle office, but I'm happy to answer questions about anything. Feel free to shoot me an email (in my profile), or comment here.
I wanted to highlight a few specific positions we're looking for:
* Dev. Platform Software Engineer: This is the team I work on. We strongly believe that there is a use for Splunk outside of logging, and we're enabling the usage of the technology for dealing with large quantities of data, whether it's for social network analysis, cloud management or anything in between. http://www.splunk.com/view/SP-
CAAAGK3?jvi=oHkCVfwi
* Cloud Software Engineer: we're developing the next stage of our product, which is a hosted version of Splunk in the cloud, with all the benefits you'd expect (like automatic elastic scaling). Come help us make this a reality: http://www.splunk.com/view/SP-CAAAGK3?jvi=o4U8VfwL
* Hadoop Software Engineer: Usage of Hadoop is exploding to do batch-oriented processing on massive quantities of data. We think there is a lot of value to be had by combining the power of Splunk and Hadoop, and we're developing solutions to make this possible. http://www.splunk.com/view/SP-CAAAGK3?jvi=oqCaWfwS
* Software Engineer in Test: Splunk is a complex machine, deployed in a distributed manner, many times being used for different things. Our testing team is top notch, and helps us deliver quality releases. http://www.splunk.com/view/SP-CAAAGK3?jvi=o5ZvVfwe
* Windows QA Engineer: Splunk is putting a lot of effort into making Splunk & Windows to be a match made in heaven. We need people to help us make sure we're getting everything quite, because details matter. http://www.splunk.com/view/SP-CAAAGK3?jvi=oLpdWfw3
* Server Sustaining Engineer: Splunk is a very customer-focused company, and it's important that customers are happy with the products. The sustaining team is in charge of making sure that after major releases, we can keep customers happy for a long time. http://www.splunk.com/view/SP-CAAAGK3?jvi=obAdWfwE
Another option for time series data (with prettier graphs) is Splunk. Disclaimer: I work at Splunk, on the developer platform team, so I have a vested interest in developers trying it out and giving me feedback :)
If you're curious about it and have any questions, feel free to get in touch (email in profile).
I worked with Leftronic back in August and again last month for some demos we did at Splunk (for our SDKs), and it was a joy.
Lionel and Rajiv were always very responsive and very accepting of feedback, and they actually fixed all the problems I had found back in August. Triple-A team here :)
1. Good to know about GitPod - I haven't looked at it for a while so looks like I was outdated. The rest of what you said is good too.
2. This is mostly for ML development, where GPUs are sadly often required even for dev work.