‘Tis the season for specialty crop grant applications.Listen nowThe grants are part of the U.S. Department of Agriculture’s effort to expand certain crops and are distributed by the state Division of Agriculture.Johanna Herron with the Division of Agriculture says farmers of root vegetables, fruits and even flowers are eligible to apply.“The industry we see the most applying for proposals for the specialty crop is the peony industry, and that’s the flower industry,” Herron said. “They’ve been kind of blossoming, to put a pun out there, over the last few years and growing as a sector.”Herron said the division awards a total of about 200 thousand dollars each year.Letters of intent to apply for specialty crop grants are due Friday.
Now Bloomberg reports that the SEC is asking a judge to hold Musk in contempt for tweeting Tesla would make “around 500K” cars in 2019. On the same day of the original tweet, a few hours later, Musk amended his comment, clarifying that he meant 500,000 cars would be made on an “annualized production rate” based on 10,000 cars made per week. The tweets remained on his Twitter feed as of Monday afternoon. In fact, he continues to tweet — he posted a meme as news broke about the SEC’s actions.The SEC declined to comment beyond a 17-page motion filed Monday. In the document the SEC said it reached out to Musk and Tesla the day after the Feb. 19 tweet and found out the tweet had not been pre-approved before it went out. A Tesla lawyer actually helped Musk draft the “meant to say” tweet a few hours later as a “corrective tweet.”Musk apparently thought the Tesla earnings call in January counted as pre-approval for his comments, “because he thought he was simply recapitulating information that had already been pre-approved,” the SEC wrote.The SEC cited Musk’s 60 Minutes interview from early December in which he said, “Well I guess we might make some mistakes, who knows” and “I do not respect the SEC.”The SEC also learned through that Musk’s tweets are only reviewed after publication, and “there is no suggestion that Musk has sought or obtained pre-approval of any tweet prior to publishing it.”Here’s the full motion: Tesla made 0 cars in 2011, but will make around 500k in 2019— Elon Musk (@elonmusk) February 20, 2019 Last week, Tesla CEO Elon Musk couldn’t contain himself — he had to tweet about his electric car company.The problem? After he reached a settlement with the U.S. Securities and Exchange Commission last year over his now infamous “funding secured” tweet, he isn’t supposed to tweet about things that could impact markets and his publicly traded company without approval from Tesla. Meant to say annualized production rate at end of 2019 probably around 500k, ie 10k cars/week. Deliveries for year still estimated to be about 400k.— Elon Musk (@elonmusk) February 20, 2019 Elon Musk is in trouble for tweeting again.Image: Joshua Lott/Getty ImagesBy Sasha Lekach2019-02-26 00:01:18 UTC
Although Apache Kafka is widely adopted, there are still operational challenges that teams run into when they try to run Kafka at scale. In order to restore balance to Kafka clusters, LinkedIn open sourced and developed Cruise Control, its general-purpose system that continuously monitors clusters and automatically adjusts the resources needed to meet pre-defined performance goals.According to LinkedIn staff software engineer Jiangjie Qin in a LinkedIn engineering post, Cruise Control started off as an intern project by Efe Gencer, who is currently a research assistant at Cornell University. Several members of the Kafka development team helped to brainstorm and design Cruise Control, and the project received several other contributions from the Kafka SRE team at LinkedIn.Cruise Control for Kafka is currently deployed at LinkedIn, where it monitors user-specified goals, makes sure there are no violations of these goals, analyzes the existing workload on the cluster, and then automatically executes administrative operations to satisfy those goals, according to Qin.Cruise Control was also designed with a few requirements in mind, which meant it needed to be reliable, resource-efficient, extensible, and serve as a general framework “that could only understand the application and migrate only a partial state and be used in any stateful distributed system,” writes Qin.Cruise Control follows a monitor-analysis-action working cycle, providing a REST API for users to interact with. This REST API supports “querying the workload and optimization proposals of the Kafka cluster, as well as triggering admin operations,” according to Qin. Cruise Control is also made up of a Load Monitor, which collects standard Kafka metrics from the cluster and derives per partition resource metrics that are not available. For instance, it estimates CPU utilization on a per-partition basis, writes Qin.The Analyzer is the actual “brain” of the open source project, using a heuristic method to generate optimization proposals based on the goals and the cluster workload model from the Load Monitor.According to Qin:“Cruise Control also allows for specifying hard goals and soft goals. A hard goal is one that must be satisfied (e.g., replica placement must be rack-aware). Soft goals, on the other hand, may be left unmet if doing so makes it possible to satisfy all the hard goals. The optimization would fail if the optimized results violate a hard goal. Usually, the hard goals will have a higher priority than the soft goals.”Now that Cruise Control is open sourced, Kafka users can check out its architecture and what challenges it aims to solve. LinkedIn recommends users check this reference for a guide.